The heavy oxygen isotope (18O) could be provided to plants either in the CO2 or in H2O or in both. Today, we know from experimental results that O2 released from chloroplasts comes from H2O and not from CO2. Which of the following experimental results supports this finding? Select one: When heavy oxygen is part of water given to the plant, the plant produces heavy O2. When heavy oxygen is part of CO2 given to the plant, the plant produces heavy O2. When heavy oxygen is part of both water and CO2 given a plant, the plant produces heavy O2. When no heavy oxygen is part of water given the plant, the plant produces no heavy O2. When no heavy oxygen is part of CO2 given the plant, the plant produces no heavy O2.

The heavy oxygen isotope (18O) could be provided to plants either in the CO2 or in H2O or in both. Today, we know from experimental results that O2 released from chloroplasts comes from H2O and not from CO2. Which of the following experimental results supports this finding? Select one: When heavy oxygen is part of water given to the plant, the plant produces heavy O2. When heavy oxygen is part of CO2 given to the plant, the plant produces heavy O2. When heavy oxygen is part of both water and CO2 given a plant, the plant produces heavy O2. When no heavy oxygen is part of water given the plant, the plant produces no heavy O2. When no heavy oxygen is part of CO2 given the plant, the plant produces no heavy O2.

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Researchers recently investigated whether or not coffee prevented the development of high blood sugar (hyperglycemia) in laboratory mice. The mice used in this experiment have a mutation that makes them become diabetic. Read about this research study in this article published on the Science Daily web-site New Evidence That Drinking Coffee May Reduce the Risk of Diabetes as well as the following summary: A group of 11 mice was given water, and another group of 10 mice was supplied with diluted black coffee (coffee:water 1:1) as drinking fluids for five weeks. The composition of the diets and living conditions were similar for both groups of mice. Blood glucose was monitored weekly for all mice. After five weeks, there was no change in average body weight between groups. Results indicated that blood glucose concentrations increased significantly in the mice that drank water compared with those that were supplied with coffee. Finally, blood glucose concentration in the coffee group exhibited a 30 percent decrease compared with that in the water group. In the original paper, the investigators acknowledged that the coffee for the experiment was supplied as a gift from a corporation. Then answer the following questions in your own words: 1. Identify and describe the steps of the scientific method. Which observations do you think the scientists made leading up to this research study? Given your understanding of the experimental design, formulate a specific hypothesis that is being tested in this experiment. Describe the experimental design including control and treatment group(s), and dependent and independent variables. Summarize the results and the conclusion (50 points) 2. Criticize the research described. Things to consider: Were the test subjects and treatments relevant and appropriate? Was the sample size large enough? Were the methods used appropriate? Can you think of a potential bias in a research study like this? What are the limitations of the conclusions made in this research study? Address at least two of these questions in your critique of the research study (20 points). 3. Discuss the relevance of this type of research, both for the world in general and for you personally (20 points). 4. Write answers in your own words with proper grammar and spelling (10 points)

Researchers recently investigated whether or not coffee prevented the development of high blood sugar (hyperglycemia) in laboratory mice. The mice used in this experiment have a mutation that makes them become diabetic. Read about this research study in this article published on the Science Daily web-site New Evidence That Drinking Coffee May Reduce the Risk of Diabetes as well as the following summary: A group of 11 mice was given water, and another group of 10 mice was supplied with diluted black coffee (coffee:water 1:1) as drinking fluids for five weeks. The composition of the diets and living conditions were similar for both groups of mice. Blood glucose was monitored weekly for all mice. After five weeks, there was no change in average body weight between groups. Results indicated that blood glucose concentrations increased significantly in the mice that drank water compared with those that were supplied with coffee. Finally, blood glucose concentration in the coffee group exhibited a 30 percent decrease compared with that in the water group. In the original paper, the investigators acknowledged that the coffee for the experiment was supplied as a gift from a corporation. Then answer the following questions in your own words: 1. Identify and describe the steps of the scientific method. Which observations do you think the scientists made leading up to this research study? Given your understanding of the experimental design, formulate a specific hypothesis that is being tested in this experiment. Describe the experimental design including control and treatment group(s), and dependent and independent variables. Summarize the results and the conclusion (50 points) 2. Criticize the research described. Things to consider: Were the test subjects and treatments relevant and appropriate? Was the sample size large enough? Were the methods used appropriate? Can you think of a potential bias in a research study like this? What are the limitations of the conclusions made in this research study? Address at least two of these questions in your critique of the research study (20 points). 3. Discuss the relevance of this type of research, both for the world in general and for you personally (20 points). 4. Write answers in your own words with proper grammar and spelling (10 points)

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“No Bats in the Belfry” by Dechaine and Johnson Page 1 by Jennifer M. Dechaine1,2 and James E. Johnson1 1Department of Biological Sciences 2Department of Science Education Central Washington University, Ellensburg, WA NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE Part I – The Basic Question Introduction Imagine going out for a brisk winter snowshoe and suddenly stumbling upon hundreds of bat carcasses littering the forest floor. Unfortunately, this unsettling sight has become all too common in the United States (Figure 1). White-nose syndrome (WNS), first discovered in 2006, has now spread to 20 states and has led to the deaths of over 5.5 million bats (as of January 2012). WNS is a disease caused by the fungus, Pseudogymnoascus destructans. Bats infected with WNS develop white fuzz on their noses (Figure 2, next page) and often exhibit unnatural behavior, such as flying outside during the winter when they should be hibernating. WNS affects at least six different bat species in the United States and quickly decimates bat populations (colony mortality is commonly greater than 90%). Scientists have predicted that if deaths continue at the current rate, several bat species will become locally extinct within 20 years. Bats provide natural pest control by eating harmful insects, such as crop pests and disease carrying insect species, and losing bat populations would have devastating consequences for the U.S. economy. Researchers have sprung into action to study how bats become infected with and transmit P. destructans, but a key component of this research is determining where the fungus came from in the first place. Some have suggested that it is an invasive species from a different country while others think it is a North American fungal species that has recently become better able to cause disease. In this case study, we examine the origin of P. destructans causing WNS in North America. Some Other Important Observations • WNS was first documented at four cave sites in New York State in 2006. • The fungus can be spread among bats by direct contact or spores can be transferred between caves by humans (on clothing) or other animals. • European strains of the fungus occur in low levels across Europe but have led to few bat deaths there. • Bats with WNS frequently awake during hibernation, causing them to use important fat reserves, leading to death. No Bats in the Belfry: The Origin of White- Nose Syndrome in Little Brown Bats Figure 1. Many bats dead in winter from white-nose syndrome. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 2 Questions 1. What is the basic question of this study and why is it interesting? 2. What specific testable hypotheses can you develop to explain the observations and answer the basic question of this study? Write at least two alternative hypotheses. 3. What predictions about the effects of European strains of P. destructans on North American bats can you make if your hypotheses are correct? Write at least one prediction for each of your hypotheses. Figure 2. White fuzz on the muzzle of a little brown bat indicating infection by the disease. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 3 Part II – The Hypothesis As discussed in Part I, researchers had preliminary data suggesting that the pathogen causing WNS is an invasive fungal species (P. destructans) brought to North America from Europe. They had also observed that P. destructans occurs on European bats but rarely causes their death. Preliminary research also suggested that one reason that bats have been dying from WNS is that the disorder arouses them from hibernation, causing the bats to waste fat reserves flying during the winter when food is not readily available. These observations led researchers to speculate that European P. destructans will affect North American bat hibernation at least as severely as does North American P. destructans (Warnecke et al. 2012). Questions 1. Explicitly state the researchers’ null (H0 ) and alternative hypotheses (HA) for this study. 2. Describe an experiment you could use to differentiate between these hypotheses (H0 and HA). NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 4 Part III – Experiments and Observations In 2010, Lisa Warnecke and colleagues (2012) isolated P. destructans fungal spores from Europe and North America. They collected 54 male little brown bats (Myotis lucifugus) from the wild and divided these bats equally into three treatment groups. • Group 1 was inoculated with the North American P. destructans spores (NAGd treatment). • Group 2 was inoculated with the European P. destructans spores (EUGd treatment). • Group 3 was inoculated using the inoculation serum with no spores (Control treatment). All three groups were put into separate dark chambers that simulated the environmental conditions of a cave. All bats began hibernating within the first week of the study. The researchers used infrared cameras to examine the bats’ hibernation over four consecutive intervals of 26 days each. They then used the cameras to determine the total number of times a bat was aroused from hibernation during each interval. Questions 1. Use the graph below to predict what the results will look like if the null hypothesis is supported. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justifiy your predictions. 2. Use the graph below to predict what the results will look like if the null hypothesis is rejected. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justify your predictions. Null Supported Total Arousal counts Interval Null Rejected Total Arousal counts Interval NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 5 2 Credits: Title block photo by David A. Riggs (http://www.flickr.com/photos/driggs/6933593833/sizes/l/), cropped, used in accordance with CC BY-SA 2.0 (http://creativecommons.org/licenses/by-sa/2.0/). Figure 1 photo by Kevin Wenner/Pennsylvania Game Commision (http://www. portal.state.pa.us/portal/server.pt/document/901415/white-nose_kills_hundreds_of_bats_in_lackawanna_county_pdf ). Figure 2 photo courtesy of Ryan von Linden/New York Department of Environmental Conservation, http://www.flickr.com/photos/usfwshq/5765048289/sizes/l/in/ set-72157626818845664/, used in accordance with CC BY 2.0 (http://creativecommons.org/licenses/by/2.0/deed.en). Case copyright held by the National Center for Case Study Teaching in Science, University at Buffalo, State University of New York. Originally published February 6, 2014. Please see our usage guidelines, which outline our policy concerning permissible reproduction of this work. Part IV – Results Figure 3 (below) shows the real data from the study. There is no data for interval 4 bats that were exposed to the European P. destructans (gray bar) because all of the bats in that group died. Questions 1. How do your predictions compare with the experimental results? Be specific. 2. Do the results support or reject the null hypothesis? 3. If the European P. destructans is causing WNS in North America, how come European bats aren’t dying from the same disease? References U.S. Fish and Wildlife Service. 2012. White-Nose Syndrome. Available at: http://whitenosesyndrome.org/. Last accessed December 20, 2013. Warnecke, L., et al. 2012. Inoculation of bats with European Geomyces destructans supports the novel pathogen hypothesis for the origin of white-nose syndrome. PNAS Online Early Edition: http://www.pnas.org/cgi/ doi/10.1073/pnas.1200374109. Last accessed December 20, 2013. Figure 3. Changes in hibernation patterns in M. lucifugus following inoculation with North American P. destructans (NAGd), European P. destructans (EUGd), or the control serum. Interval Total Arousal counts

“No Bats in the Belfry” by Dechaine and Johnson Page 1 by Jennifer M. Dechaine1,2 and James E. Johnson1 1Department of Biological Sciences 2Department of Science Education Central Washington University, Ellensburg, WA NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE Part I – The Basic Question Introduction Imagine going out for a brisk winter snowshoe and suddenly stumbling upon hundreds of bat carcasses littering the forest floor. Unfortunately, this unsettling sight has become all too common in the United States (Figure 1). White-nose syndrome (WNS), first discovered in 2006, has now spread to 20 states and has led to the deaths of over 5.5 million bats (as of January 2012). WNS is a disease caused by the fungus, Pseudogymnoascus destructans. Bats infected with WNS develop white fuzz on their noses (Figure 2, next page) and often exhibit unnatural behavior, such as flying outside during the winter when they should be hibernating. WNS affects at least six different bat species in the United States and quickly decimates bat populations (colony mortality is commonly greater than 90%). Scientists have predicted that if deaths continue at the current rate, several bat species will become locally extinct within 20 years. Bats provide natural pest control by eating harmful insects, such as crop pests and disease carrying insect species, and losing bat populations would have devastating consequences for the U.S. economy. Researchers have sprung into action to study how bats become infected with and transmit P. destructans, but a key component of this research is determining where the fungus came from in the first place. Some have suggested that it is an invasive species from a different country while others think it is a North American fungal species that has recently become better able to cause disease. In this case study, we examine the origin of P. destructans causing WNS in North America. Some Other Important Observations • WNS was first documented at four cave sites in New York State in 2006. • The fungus can be spread among bats by direct contact or spores can be transferred between caves by humans (on clothing) or other animals. • European strains of the fungus occur in low levels across Europe but have led to few bat deaths there. • Bats with WNS frequently awake during hibernation, causing them to use important fat reserves, leading to death. No Bats in the Belfry: The Origin of White- Nose Syndrome in Little Brown Bats Figure 1. Many bats dead in winter from white-nose syndrome. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 2 Questions 1. What is the basic question of this study and why is it interesting? 2. What specific testable hypotheses can you develop to explain the observations and answer the basic question of this study? Write at least two alternative hypotheses. 3. What predictions about the effects of European strains of P. destructans on North American bats can you make if your hypotheses are correct? Write at least one prediction for each of your hypotheses. Figure 2. White fuzz on the muzzle of a little brown bat indicating infection by the disease. NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 3 Part II – The Hypothesis As discussed in Part I, researchers had preliminary data suggesting that the pathogen causing WNS is an invasive fungal species (P. destructans) brought to North America from Europe. They had also observed that P. destructans occurs on European bats but rarely causes their death. Preliminary research also suggested that one reason that bats have been dying from WNS is that the disorder arouses them from hibernation, causing the bats to waste fat reserves flying during the winter when food is not readily available. These observations led researchers to speculate that European P. destructans will affect North American bat hibernation at least as severely as does North American P. destructans (Warnecke et al. 2012). Questions 1. Explicitly state the researchers’ null (H0 ) and alternative hypotheses (HA) for this study. 2. Describe an experiment you could use to differentiate between these hypotheses (H0 and HA). NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 4 Part III – Experiments and Observations In 2010, Lisa Warnecke and colleagues (2012) isolated P. destructans fungal spores from Europe and North America. They collected 54 male little brown bats (Myotis lucifugus) from the wild and divided these bats equally into three treatment groups. • Group 1 was inoculated with the North American P. destructans spores (NAGd treatment). • Group 2 was inoculated with the European P. destructans spores (EUGd treatment). • Group 3 was inoculated using the inoculation serum with no spores (Control treatment). All three groups were put into separate dark chambers that simulated the environmental conditions of a cave. All bats began hibernating within the first week of the study. The researchers used infrared cameras to examine the bats’ hibernation over four consecutive intervals of 26 days each. They then used the cameras to determine the total number of times a bat was aroused from hibernation during each interval. Questions 1. Use the graph below to predict what the results will look like if the null hypothesis is supported. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justifiy your predictions. 2. Use the graph below to predict what the results will look like if the null hypothesis is rejected. The total arousal counts in the control treatment at each interval is graphed for you (open bars). Justify your predictions. Null Supported Total Arousal counts Interval Null Rejected Total Arousal counts Interval NATIONAL CENTER FOR CASE STUDY TEACHING IN SCIENCE “No Bats in the Belfry” by Dechaine and Johnson Page 5 2 Credits: Title block photo by David A. Riggs (http://www.flickr.com/photos/driggs/6933593833/sizes/l/), cropped, used in accordance with CC BY-SA 2.0 (http://creativecommons.org/licenses/by-sa/2.0/). Figure 1 photo by Kevin Wenner/Pennsylvania Game Commision (http://www. portal.state.pa.us/portal/server.pt/document/901415/white-nose_kills_hundreds_of_bats_in_lackawanna_county_pdf ). Figure 2 photo courtesy of Ryan von Linden/New York Department of Environmental Conservation, http://www.flickr.com/photos/usfwshq/5765048289/sizes/l/in/ set-72157626818845664/, used in accordance with CC BY 2.0 (http://creativecommons.org/licenses/by/2.0/deed.en). Case copyright held by the National Center for Case Study Teaching in Science, University at Buffalo, State University of New York. Originally published February 6, 2014. Please see our usage guidelines, which outline our policy concerning permissible reproduction of this work. Part IV – Results Figure 3 (below) shows the real data from the study. There is no data for interval 4 bats that were exposed to the European P. destructans (gray bar) because all of the bats in that group died. Questions 1. How do your predictions compare with the experimental results? Be specific. 2. Do the results support or reject the null hypothesis? 3. If the European P. destructans is causing WNS in North America, how come European bats aren’t dying from the same disease? References U.S. Fish and Wildlife Service. 2012. White-Nose Syndrome. Available at: http://whitenosesyndrome.org/. Last accessed December 20, 2013. Warnecke, L., et al. 2012. Inoculation of bats with European Geomyces destructans supports the novel pathogen hypothesis for the origin of white-nose syndrome. PNAS Online Early Edition: http://www.pnas.org/cgi/ doi/10.1073/pnas.1200374109. Last accessed December 20, 2013. Figure 3. Changes in hibernation patterns in M. lucifugus following inoculation with North American P. destructans (NAGd), European P. destructans (EUGd), or the control serum. Interval Total Arousal counts

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Watch this video and answer the multi choices: https://www.youtube.com/watch?v=D4lB4SowAQA PART 1 _______1. Sociologists obtained their knowledge of human behavior through _______, which is this process of systematically collecting information for the purpose of testing an existing theory or generating a new one. a. Common sense ideas b. Research c. Myths d. scientific laws _______2. With ____Research, the goal is scientific objectivity, and the focus is on data that can be measured numerically a. qualitative b. observational c. c. quantitative d. d. explanatory _______3. With _______research, interpretative description (words) rather than statistics (numbers) are used to analyze underlying meaning and patterns of social relationships. a. qualitative b. observational c. quantitative d. explanatory _______4. Researchers in one study systematically analyzed the contents of the notes of suicide victims to determine recurring themes, such as feeling of despair or failure. They hoped to determine if any patterns could be found that would help in understating why people might kill themselves. This is an example of __________. a. Qualitative research b. Explanatory research c. Quantitative research d. Descriptive research ______5. the first step in the research process is to: a. select and define the research problem b. review previous research. c. develop a research design d. formulate the hypothesis ______6. A_____sample is a selection from a larger population and has the essential characteristics of the total population. a. selective b. random c. representative d. longitudinal _______7. _________is the extent to which a study or research instrument accurately measures what it is supposed to measure;_________is the extent to which a study or research instrument yields consistent results. a. Validity; replication b. Replication; validity c. Validity; reliability d. Reliability; validity _______8. Researchers who use existing material and analyze data that originally was collected by others are engaged in: a. unethical conduct b. primary analysis. c. secondary analysis d. survey analysis _______9. In an experiment, the subjects in the control group a. are exposed to the independent variable. b. are not exposed to the independent variable. c. are exposed to the dependent variable. d. are not exposed to the dependent variable. _______10. A tentative statement that predicts the relationship between variable is called a. a hypothesis b. a research model. c. a probability sample. d. a generalization. ______11. John wants to test this idea: “people who attend church regularly are less likely to express prejudice toward other races than people who do not attend church regularly.’ This idea is John’s a. hypothesis. b. research model. c. conclusion. d. operational definition _______12. In a research project, which of the following steps would come after the other three? a. choosing a research design b. reviewing the literature c. formulating a hypothesis d. collecting the data ________13. The variable hypothesized to cause or influence another is called the a. dependent variable. b. hypothetical variable c. correlation variable d. independent variable ________14. An explanation of an abstract concept that is specific enough to allow a research to measure the concept is a a. Hypothesis b. correlation. c. operatonal definition. d. variable _____15. Observation, ethnography, and case studies are examples of: a. survey research b. experiments. c. Secondary analysis of existing data. d. Field research. ______16. Theory and research are interrelated because a. theory always precedes research. b. research always precedes theory c. both put limits on each other. d. they are parts of a constant cycle. ______17. A dependent variable is one that a. always occurs first. b. is influenced by another variable. c. Causes another variable to change. d. is the most important ______18. In a study designed to test the relationship between gender and voting behavior, the independent variable would be a. the age of the candidates b. voting behavior. c. The political party of the candidates. d. Gender ______19. Differences in age, sex, race, and social class are treated as ____________in sociological research. a. variables b. references c. causes d. controls ______20. Researchers in agriculture decided to test the effects of a new fertilizer on crop growth. In this study, crop growth is the a. independent variable b. dependent variable c. control variable d. correlation e. _____21. The ______is appropriate for studying the relationships among variables under carefully controlled conditions. a. experiment b. survey c. observational study d. in-depth study _____22. In every experiment, some subjects are exposed to an independent variable, and are then watched closely for their reactions. These subjects are known as the a. reference group b. experimental group c. control group d. survey group. ______23. A usual research method for learning the attitudes of a population would be a. an experiment. b. A survey. c. An observational study. d. Content analysis ______24. In survey research, the total group of people the researcher is interested in is called a. the population b. the sample, c. the control group d. the random sample ______25. In the experiment method, the subjects who are exposed to all the experimental conditions except the independent variable are referred to as the_________________group. a. peer b. alternate c. control d. experimental ______26. A__________Sample is one in which every member of the population in The population has an equal chance of being selected. a. defined b. random c. purposive d. convenience ______27. A sociologist is following the research model outlined in the text. After reviewing the literature, the next step will be to a. find a suitable subject b. formulate a hypothesis c. collect the data. d. Choose a research design. ______28. Sociologists use two approaches when answering important questions. a. Explanatory and descriptive Approaches b. Direct and systematic Approaches c. Normative and systematic Approaches d. Normative and Empirical Approaches ______29. Sociologists use types of empirical studies a. Research and Theoretical Studies b. Descriptive and Explanatory Studies c. Hypothesis and Correlations Studies d. Longitudinal and Cross-sectional Studies ______30. The deductive approach begin with the a. Collecting data b. Theory and uses research to test the theory. c. Hypothesis d. Observation ______31. The inductive approach begin with a a. Theory b. Data Collection c. Reviewing the Literature d. The Problem State ______32. Quantitative Research deals with a. Words b. Numbers c. Interpretive descriptive d. Use number to analyze underlying meanings and patterns of social relationships. ______33. ________is the study of social life in its natural setting: observing and interviewing people where they live, work, and play. a. The survey b. Secondary analysis c. Field research d. The experiment ______34. ________refers to the process of collecting data while being part of the activities of the group that the researcher is studying a. The experiment b. Survey research c. Participant observation d. Secondary analysis _______35. A/an________is a detailed study of the life and activities of a group of people by researchers who may live with that group over a period of years. a. Correlational study b. ethnography c. experiment d. content analysis _______36. A/an _________is a carefully designed situation in which the researcher studies the impact of certain variables on subjects’ attitudes or behavior. a. case study b. correlational study c. experiment d. Participant observation _______37. In an experiment, the_______contains the subjects who are exposed to an independent variable to study its effect on them. a. Experiment group b. Dependent group c. Control group d. Independent group _______38. In an experiment, the_________contains the subjects who are not exposed to the independent variable. a. Experimental group b. Independent group c. Dependent group d. Control group _______39. ________is the extent to which a study or research instrument accurately measures what it is supposed to measure a. Validity b. Reliability c. Predictability d. Variability ______40. ________is the extent to which a study or research instrument yields consistent results when applied to different individual at one time or to same individuals over time. a. Validity b. Reliability c. Predictability d. Variability TRUE/FALSE ______41. In social science research, individuals are the most typical units of analysis. ______42. With qualitative research, statistics are used to analyze patterns of social relationship. ______43. Reliability is when a study gives consistent results to different research over time.

Watch this video and answer the multi choices: https://www.youtube.com/watch?v=D4lB4SowAQA PART 1 _______1. Sociologists obtained their knowledge of human behavior through _______, which is this process of systematically collecting information for the purpose of testing an existing theory or generating a new one. a. Common sense ideas b. Research c. Myths d. scientific laws _______2. With ____Research, the goal is scientific objectivity, and the focus is on data that can be measured numerically a. qualitative b. observational c. c. quantitative d. d. explanatory _______3. With _______research, interpretative description (words) rather than statistics (numbers) are used to analyze underlying meaning and patterns of social relationships. a. qualitative b. observational c. quantitative d. explanatory _______4. Researchers in one study systematically analyzed the contents of the notes of suicide victims to determine recurring themes, such as feeling of despair or failure. They hoped to determine if any patterns could be found that would help in understating why people might kill themselves. This is an example of __________. a. Qualitative research b. Explanatory research c. Quantitative research d. Descriptive research ______5. the first step in the research process is to: a. select and define the research problem b. review previous research. c. develop a research design d. formulate the hypothesis ______6. A_____sample is a selection from a larger population and has the essential characteristics of the total population. a. selective b. random c. representative d. longitudinal _______7. _________is the extent to which a study or research instrument accurately measures what it is supposed to measure;_________is the extent to which a study or research instrument yields consistent results. a. Validity; replication b. Replication; validity c. Validity; reliability d. Reliability; validity _______8. Researchers who use existing material and analyze data that originally was collected by others are engaged in: a. unethical conduct b. primary analysis. c. secondary analysis d. survey analysis _______9. In an experiment, the subjects in the control group a. are exposed to the independent variable. b. are not exposed to the independent variable. c. are exposed to the dependent variable. d. are not exposed to the dependent variable. _______10. A tentative statement that predicts the relationship between variable is called a. a hypothesis b. a research model. c. a probability sample. d. a generalization. ______11. John wants to test this idea: “people who attend church regularly are less likely to express prejudice toward other races than people who do not attend church regularly.’ This idea is John’s a. hypothesis. b. research model. c. conclusion. d. operational definition _______12. In a research project, which of the following steps would come after the other three? a. choosing a research design b. reviewing the literature c. formulating a hypothesis d. collecting the data ________13. The variable hypothesized to cause or influence another is called the a. dependent variable. b. hypothetical variable c. correlation variable d. independent variable ________14. An explanation of an abstract concept that is specific enough to allow a research to measure the concept is a a. Hypothesis b. correlation. c. operatonal definition. d. variable _____15. Observation, ethnography, and case studies are examples of: a. survey research b. experiments. c. Secondary analysis of existing data. d. Field research. ______16. Theory and research are interrelated because a. theory always precedes research. b. research always precedes theory c. both put limits on each other. d. they are parts of a constant cycle. ______17. A dependent variable is one that a. always occurs first. b. is influenced by another variable. c. Causes another variable to change. d. is the most important ______18. In a study designed to test the relationship between gender and voting behavior, the independent variable would be a. the age of the candidates b. voting behavior. c. The political party of the candidates. d. Gender ______19. Differences in age, sex, race, and social class are treated as ____________in sociological research. a. variables b. references c. causes d. controls ______20. Researchers in agriculture decided to test the effects of a new fertilizer on crop growth. In this study, crop growth is the a. independent variable b. dependent variable c. control variable d. correlation e. _____21. The ______is appropriate for studying the relationships among variables under carefully controlled conditions. a. experiment b. survey c. observational study d. in-depth study _____22. In every experiment, some subjects are exposed to an independent variable, and are then watched closely for their reactions. These subjects are known as the a. reference group b. experimental group c. control group d. survey group. ______23. A usual research method for learning the attitudes of a population would be a. an experiment. b. A survey. c. An observational study. d. Content analysis ______24. In survey research, the total group of people the researcher is interested in is called a. the population b. the sample, c. the control group d. the random sample ______25. In the experiment method, the subjects who are exposed to all the experimental conditions except the independent variable are referred to as the_________________group. a. peer b. alternate c. control d. experimental ______26. A__________Sample is one in which every member of the population in The population has an equal chance of being selected. a. defined b. random c. purposive d. convenience ______27. A sociologist is following the research model outlined in the text. After reviewing the literature, the next step will be to a. find a suitable subject b. formulate a hypothesis c. collect the data. d. Choose a research design. ______28. Sociologists use two approaches when answering important questions. a. Explanatory and descriptive Approaches b. Direct and systematic Approaches c. Normative and systematic Approaches d. Normative and Empirical Approaches ______29. Sociologists use types of empirical studies a. Research and Theoretical Studies b. Descriptive and Explanatory Studies c. Hypothesis and Correlations Studies d. Longitudinal and Cross-sectional Studies ______30. The deductive approach begin with the a. Collecting data b. Theory and uses research to test the theory. c. Hypothesis d. Observation ______31. The inductive approach begin with a a. Theory b. Data Collection c. Reviewing the Literature d. The Problem State ______32. Quantitative Research deals with a. Words b. Numbers c. Interpretive descriptive d. Use number to analyze underlying meanings and patterns of social relationships. ______33. ________is the study of social life in its natural setting: observing and interviewing people where they live, work, and play. a. The survey b. Secondary analysis c. Field research d. The experiment ______34. ________refers to the process of collecting data while being part of the activities of the group that the researcher is studying a. The experiment b. Survey research c. Participant observation d. Secondary analysis _______35. A/an________is a detailed study of the life and activities of a group of people by researchers who may live with that group over a period of years. a. Correlational study b. ethnography c. experiment d. content analysis _______36. A/an _________is a carefully designed situation in which the researcher studies the impact of certain variables on subjects’ attitudes or behavior. a. case study b. correlational study c. experiment d. Participant observation _______37. In an experiment, the_______contains the subjects who are exposed to an independent variable to study its effect on them. a. Experiment group b. Dependent group c. Control group d. Independent group _______38. In an experiment, the_________contains the subjects who are not exposed to the independent variable. a. Experimental group b. Independent group c. Dependent group d. Control group _______39. ________is the extent to which a study or research instrument accurately measures what it is supposed to measure a. Validity b. Reliability c. Predictability d. Variability ______40. ________is the extent to which a study or research instrument yields consistent results when applied to different individual at one time or to same individuals over time. a. Validity b. Reliability c. Predictability d. Variability TRUE/FALSE ______41. In social science research, individuals are the most typical units of analysis. ______42. With qualitative research, statistics are used to analyze patterns of social relationship. ______43. Reliability is when a study gives consistent results to different research over time.

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Morgan Extra Pages Graphing with Excel to be carried out in a computer lab, 3rd floor Calloway Hall or elsewhere The Excel spreadsheet consists of vertical columns and horizontal rows; a column and row intersect at a cell. A cell can contain data for use in calculations of all sorts. The Name Box shows the currently selected cell (Fig. 1). In the Excel 2007 and 2010 versions the drop-down menus familiar in most software screens have been replaced by tabs with horizontally-arranged command buttons of various categories (Fig. 2) ___________________________________________________________________ Open Excel, click on the Microsoft circle, upper left, and Save As your surname. xlsx on the desktop. Before leaving the lab e-mail the file to yourself and/or save to a flash drive. Also e-mail it to your instructor. Figure 1. Parts of an Excel spreadsheet. Name Box Figure 2. Tabs. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 1: BASIC OPERATIONS Click Save often as you work. 1. Type the heading “Edge Length” in Cell A1 and double click the crack between the A and B column heading for automatic widening of column A. Similarly, write headings for columns B and C and enter numbers in Cells A2 and A3 as in Fig. 3. Highlight Cells A2 and A3 by dragging the cursor (chunky plus-shape) over the two of them and letting go. 2. Note that there are three types of cursor crosses: chunky for selecting, barbed for moving entries or blocks of entries from cell to cell, and tiny (appearing only at the little square in the lower-right corner of a cell). Obtain a tiny arrow for Cell A3 and perform a plus-drag down Column A until the cells are filled up to 40 (in Cell A8). Note that the two highlighted cells set both the starting value of the fill and the intervals. 3. Click on Cell B2 and enter a formula for face area of a cube as follows: type =, click on Cell A2, type ^2, and press Enter (note the formula bar in Fig. 4). 4. Enter the formula for cube volume in Cell C2 (same procedure, but “=, click on A2, ^3, Enter”). 5. Highlight Cells B2 and C2; plus-drag down to Row 8 (Fig. 5). Do the numbers look correct? Click on some cells in the newly filled area and notice how Excel steps the row designations as it moves down the column (it can do it for horizontal plusdrags along rows also). This is the major programming development that has led to the popularity of spreadsheets. Figure 3. Entries. Figure 4. A formula. Figure 5. Plus-dragging formulas. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com 6. Now let’s graph the Face Area versus Edge Length: select Cells A1 through B8, choose the Insert tab, and click the Scatter drop-down menu and select “Scatter with only Markers” (Fig. 6). 7. Move the graph (Excel calls it a “chart”) that appears up alongside your number table and dress it up as follows: a. Note that some Chart Layouts have appeared above. Click Layout 1 and alter each title to read Face Area for the vertical axis, Edge Length for the horizontal and Face Area vs. Edge Length for the Graph Title. b. Activate the Excel Least squares routine, called “fitting a trendline” in the program: right click any of the data markers and click Add Trendline. Choose Power and also check “Display equation on chart” and “Display R-squared value on chart.” Fig. 7 shows what the graph will look like at this point. c. The titles are explicit, so the legend is unnecessary. Click on it and press the delete button to remove it. Figure 6. Creating a scatter graph. Figure 7. A graph with a fitted curve. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com 8. Now let’s overlay the Volume vs. Edge Length curve onto the same graph (optional for 203L/205L): Make a copy of your graph by clicking on the outer white area, clicking ctrl-c (or right click, copy), and pasting the copy somewhere else (ctrl-v). If you wish, delete the trendline as in Fig. 8. a. Right click on the outer white space, choose Select Data and click the Add button. b. You can type in the cell ranges by hand in the dialog box that comes up, but it is easier to click the red, white, and blue button on the right of each space and highlight what you want to go in. Click the red, white, and blue of the bar that has appeared, and you will bounce back to the Add dialog box. Use the Edge Length column for the x’s and Volume for the y’s. c. Right-click on any volume data point and choose Format Data Series. Clicking Secondary Axis will place its scale on the right of the graph as in Fig. 8. d. Dress up your graph with two axis titles (Layout-Labels-Axis Titles), etc. Figure 8. Adding a second curve and y-axis to the graph Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 2: INTERPRETING A LINEAR GRAPH Introduction: Many experiments are repeated a number of times with one of the parameters involved varied from run to run. Often the goal is to measure the rate of change of a dependent variable, rather than a particular value. If the dependent variable can be expressed as a linear function of the independent parameter, then the slope and yintercept of an appropriate graph will give the rate of change and a particular value, respectively. An example of such an experiment in PHYS.203L/205L is the first part of Lab 20, in which weights are added to the bottom of a suspended spring (Figure 9). This experiment shows that a spring exerts a force Fs proportional to the distance stretched y = (y-yo), a relationship known as Hooke’s Law: Fs = – k(y – yo) (Eq. 1) where k is called the Hooke’s Law constant. The minus sign shows that the spring opposes any push or pull on it. In Lab 20 Fs is equal to (- Mg) and y is given by the reading on a meter stick. Masses were added to the bottom of the spring in 50-g increments giving weights in newtons of 0.49, 0.98, etc. The weight pan was used as the pointer for reading y and had a mass of 50 g, so yo could not be directly measured. For convenient graphing Equation 1 can be rewritten: -(Mg) = – ky + kyo Or (Mg) = ky – kyo (Eq. 1′) Procedure 1. On your spreadsheet note the tabs at the bottom left and double-click Sheet1. Type in “Basics,” and then click the Sheet2 tab to bring up a fresh worksheet. Change the sheet name to “Linear Fit” and fill in data as in this table. Hooke’s Law Experiment y (m) -Fs = Mg (N) 0.337 0.49 0.388 0.98 0.446 1.47 0.498 1.96 0.550 2.45 2. Highlight the cells with the numbers, and graph (Mg) versus y as in Steps 6 and 7 of the Basics section. Your Trendline this time will be Linear of course. If you are having trouble remembering what’s versus what, “y” looks like “v”, so what comes before the “v” of “versus” goes on the y (vertical) axis. Yes, this graph is confusing: the horizontal (“x”) axis is distance y, and the “y” axis is something else. 3. Click on the Equation/R2 box on the graph and highlight just the slope, that is, only the number that comes before the “x.” Copy it (control-c is a fast way to Figure 9. A spring with a weight stretching it Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com do it) and paste it (control-v) into an empty cell. Do likewise for the intercept (including the minus sign). SAVE YOUR FILE! 5. The next steps use the standard procedure for obtaining information from linear data. Write the general equation for a straight line immediately below a hand-written copy of Equation 1′ then circle matching items: (Mg) = k y + (- k yo) (Eq. 1′) y = m x + b Note the parentheses around the intercept term of Equation 1′ to emphasize that the minus sign is part of it. Equating above and below, you can create two useful new equations: slope m = k (Eq. 2) y-intercept b = -kyo (Eq. 3) 6. Solve Equation 2 for k, that is, rewrite left to right. Then substitute the value for slope m from your graph, and you have an experimental value for the Hooke’s Law constant k. Next solve Equation 3 for yo, substitute the value for intercept b from your graph and the value of k that you just found, and calculate yo. 7. Examine your linear graph for clues to finding the units of the slope and the yintercept. Use these units to find the units of k and yo. 8. Present your values of k and yo with their units neatly at the bottom of your spreadsheet. 9. R2 in Excel, like r in our lab manual and Corr. in the LoggerPro software, is a measure of how well the calculated line matches the data points. 1.00 would indicate a perfect match. State how good a match you think was made in this case? 10. Do the Homework, Further Exercises on Interpreting Linear Graphs, on the following pages. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com Eq.1 M m f M a g               , (Eq.2) M slope m g       (Eq.3) M b f        Morgan Extra Pages Homework: Graph Interpretation Exercises EXAMPLE WITH COMPLETE SOLUTION In PHYS.203L and 205L we do Lab 9 Newton’s Second Law on Atwood’s Machine using a photogate sensor (Fig. 1). The Atwood’s apparatus can slow the rate of fall enough to be measured even with primitive timing devices. In our experiment LoggerPro software automatically collects and analyzes the data giving reliable measurements of g, the acceleration of gravity. The equation governing motion for Atwood’s Machine can be written: where a is the acceleration of the masses and string, g is the acceleration of gravity, M is the total mass at both ends of the string, m is the difference between the masses, and f is the frictional force at the hub of the pulley wheel. In this exercise you are given a graph of a vs. m obtained in this experiment with the values of M and the slope and intercept (Fig. 2). The goal is to extract values for acceleration of gravity g and frictional force f from this information. To analyze the graph we write y = mx + b, the general equation for a straight line, directly under Equation 1 and match up the various parameters: Equating above and below, you can create two new equations: and y m x b M m f M a g                Figure 1. The Atwood’s Machine setup (from the LoggerPro handout). Figure 2. Graph of acceleration versus mass difference; data from a Physics I experiment. Atwood’s Machine M = 0.400 kg a = 24.4 m – 0.018 R2 = 0.998 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 0.000 0.010 0.020 0.030 0.040 0.050 0.060  m (kg) a (m/s2) Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com 2 2 9.76 / 0.400 24.4 /( ) m s kg m kg s g Mm      To handle Equation 2 it pays to consider what the units of the slope are. A slope is “the rise over the run,“ so its units must be the units of the vertical axis divided by those of the horizontal axis. In this case: Now let’s solve Equation 2 for g and substitute the values of total mass M and of the slope m from the graph: Using 9.80 m/s2 as the Baltimore accepted value for g, we can calculate the percent error: A similar process with Equation 3 leads to a value for f, the frictional force at the hub of the pulley wheel. Note that the units of intercept b are simply whatever the vertical axis units are, m/s2 in this case. Solving Equation 3 for f: EXERCISE 1 The Picket Fence experiment makes use of LoggerPro software to calculate velocities at regular time intervals as the striped plate passes through the photogate (Fig. 3). The theoretical equation is v = vi + at (Eq. 4) where vi = 0 (the fence is dropped from rest) and a = g. a. Write Equation 4 with y = mx + b under it and circle matching factors as in the Example. b. What is the experimental value of the acceleration of gravity? What is its percent error from the accepted value for Baltimore, 9.80 m/s2? c. Does the value of the y-intercept make sense? d. How well did the straight Trendline match the data? 2 / 2 kg s m kg m s   0.4% 100 9.80 9.76 9.80 100 . . . %        Acc Exp Acc Error kg m s mN kg m s f Mb 7.2 10 / 7.2 0.400 ( 0.018 / ) 3 2 2           Figure 3. Graph of speed versus time as calculated by LoggerPro as a picket fence falls freely through a photogate. Picket Fence Drop y = 9.8224x + 0.0007 R2 = 0.9997 0 2 4 6 8 10 12 0 0.2 0.4 0.6 0.8 1 1.2 t (s) v (m/s) Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 2 This is an electrical example from PHYS.204L/206L, potential difference, V, versus current, I (Fig. 4). The theoretical equation is V = IR (Eq. 5) and is known as “Ohm’s Law.” The unit symbols stand for volts, V, and Amperes, A. The factor R stands for resistance and is measured in units of ohms, symbol  (capital omega). The definition of the ohm is: V (Eq. 6) By coincidence the letter symbols for potential (a quantity ) and volts (its unit) are identical. Thus “voltage” has become the laboratory slang name for potential. a. Rearrange the Ohm’s Law equation to match y = mx + b.. b. What is the experimental resistance? c. Comment on the experimental intercept: is its value reasonable? EXERCISE 3 This graph (Fig. 5) also follows Ohm’s Law, but solved for current I. For this graph the experimenter held potential difference V constant at 15.0V and measured the current for resistances of 100, 50, 40, and 30  Solve Ohm’s Law for I and you will see that 1/R is the logical variable to use on the x axis. For units, someone once jokingly referred to a “reciprocal ohm” as a “mho,” and the name stuck. a. Rearrange Equation 5 solved for I to match y = mx + b. b. What is the experimental potential difference? c. Calculate the percent difference from the 15.0 V that the experimenter set on the power supply (the instrument used for such experiments). d. Comment on the experimental intercept: is its value reasonable? Figure 4. Graph of potential difference versus current; data from a Physics II experiment. The theoretical equation, V = IR, is known as “Ohm’s Law.” Ohm’s Law y = 0.628x – 0.0275 R2 = 0.9933 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 0.5 0.6 Current, I (A) Potential difference, V (V) Figure 5. Another application of Ohm’s Law: a graph of current versus the inverse of resistance, from a different electric circuit experiment. Current versus (1/Resistance) y = 14.727x – 0.2214 R2 = 0.9938 0 100 200 300 400 500 600 5 10 15 20 25 30 35 R-1 (millimhos) I (milliamperes) Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 4 The Atwood’s Machine experiment (see the solved example above) can be done in another way: keep mass difference m the same and vary the total mass M (Fig. 6). a. Rewrite Equation 1 and factor out (1/M). b. Equate the coefficient of (1/M) with the experimental slope and solve for acceleration of gravity g. c. Substitute the values for slope, mass difference, and frictional force and calculate the experimental of g. d. Derive the units of the slope and show that the units of g come out as they should. e. Is the value of the experimental intercept reasonable? EXERCISE 5 In the previous two exercises the reciprocal of a variable was used to make the graph come out linear. In this one the trick will be to use the square root of a variable (Fig. 7). In PHYS.203L and 205L Lab 19 The Pendulum the theoretical equation is where the period T is the time per cycle, L is the length of the string, and g is the acceleration of gravity. a. Rewrite Equation 7 with the square root of L factored out and placed at the end. b. Equate the coefficient of √L with the experimental slope and solve for acceleration of gravity g. c. Substitute the value for slope and calculate the experimental of g. d. Derive the units of the slope and show that the units of g come out as they should. e. Is the value of the experimental intercept reasonable? 2 (Eq . 7) g T   L Figure 6. Graph of acceleration versus the reciprocal of total mass; data from a another Physics I experiment. Atwood’s Machine m = 0.020 kg f = 7.2 mN y = 0.1964x – 0.0735 R2 = 0.995 0.400 0.600 0.800 1.000 2.000 2.500 3.000 3.500 4.000 4.500 5.000 1/M (1/kg) a (m/s2) Effect of Pendulum Length on Period y = 2.0523x – 0.0331 R2 = 0.999 0.400 0.800 1.200 1.600 2.000 2.400 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 L1/2 (m1/2) T (s) Figure 7. Graph of period T versus the square root of pendulum length; data from a Physics I experiment. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 6 In Exercise 5 another approach would have been to square both sides of Equation 7 and plot T2 versus L. Lab 20 directs us to use that alternative. It involves another case of periodic or harmonic motion with a similar, but more complicated, equation for the period: where T is the period of the bobbing (Fig. 8), M is the suspended mass, ms is the mass of the spring, k is a measure of stiffness called the spring constant, and C is a dimensionless factor showing how much of the spring mass is effectively bobbing. a. Square both sides of Equation 8 and rearrange it to match y = mx + b. b. Write y = mx + b under your rearranged equation and circle matching factors as in the Example. c. Write two new equations analogous to Equations 2 and 3 in the Example. Use the first of the two for calculating k and the second for finding C from the data of Fig. 9. d. A theoretical analysis has shown that for most springs C = 1/3. Find the percent error from that value. e. Derive the units of the slope and intercept; show that the units of k come out as N/m and that C is dimensionless. 2 (Eq . 8) k T M Cm s    Figure 8. In Lab 20 mass M is suspended from a spring which is set to bobbing up and down, a good approximation to simple harmonic motion (SHM), described by Equation 8. Lab 20: SHM of a Spring Mass of the spring, ms = 25.1 g y = 3.0185x + 0.0197 R2 = 0.9965 0.0000 0.2000 0.4000 0.6000 0.8000 1.0000 0 0.05 0.1 0.15 0.2 0.25 0.3 M (kg) T 2 2 Figure 9. Graph of the square of the period T2 versus suspended mass M data from a Physics I experiment. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 7 This last exercise deals with an exponential equation, and the trick is to take the logarithm of both sides. In PHYS.204L/206L we do Lab 33 The RC Time Constant with theoretical equation: where V is the potential difference at time t across a circuit element called a capacitor (the  is dropped for simplicity), Vo is V at t = 0 (try it), and  (tau) is a characteristic of the circuit called the time constant. a. Take the natural log of both sides and apply the addition rule for logarithms of a product on the right-hand side. b. Noting that the graph (Fig. 10) plots lnV versus t, arrange your equation in y = mx + b order, write y = mx + b under it, and circle the parts as in the Example. c. Write two new equations analogous to Equations 2 and 3 in the Example. Use the first of the two for calculating  and the second for finding lnVo and then Vo. d. Note that the units of lnV are the natural log of volts, lnV. As usual derive the units of the slope and interecept and use them to obtain the units of your experimental V and t. V V e (Eq. 9) t o    Figure 10. Graph of a logarithm versus time; data from Lab 33, a Physics II experiment. Discharge of a Capacitor y = -9.17E-03x + 2.00E+00 R2 = 9.98E-01 0.00 0.50 1.00 1.50 2.00 2.50

Morgan Extra Pages Graphing with Excel to be carried out in a computer lab, 3rd floor Calloway Hall or elsewhere The Excel spreadsheet consists of vertical columns and horizontal rows; a column and row intersect at a cell. A cell can contain data for use in calculations of all sorts. The Name Box shows the currently selected cell (Fig. 1). In the Excel 2007 and 2010 versions the drop-down menus familiar in most software screens have been replaced by tabs with horizontally-arranged command buttons of various categories (Fig. 2) ___________________________________________________________________ Open Excel, click on the Microsoft circle, upper left, and Save As your surname. xlsx on the desktop. Before leaving the lab e-mail the file to yourself and/or save to a flash drive. Also e-mail it to your instructor. Figure 1. Parts of an Excel spreadsheet. Name Box Figure 2. Tabs. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 1: BASIC OPERATIONS Click Save often as you work. 1. Type the heading “Edge Length” in Cell A1 and double click the crack between the A and B column heading for automatic widening of column A. Similarly, write headings for columns B and C and enter numbers in Cells A2 and A3 as in Fig. 3. Highlight Cells A2 and A3 by dragging the cursor (chunky plus-shape) over the two of them and letting go. 2. Note that there are three types of cursor crosses: chunky for selecting, barbed for moving entries or blocks of entries from cell to cell, and tiny (appearing only at the little square in the lower-right corner of a cell). Obtain a tiny arrow for Cell A3 and perform a plus-drag down Column A until the cells are filled up to 40 (in Cell A8). Note that the two highlighted cells set both the starting value of the fill and the intervals. 3. Click on Cell B2 and enter a formula for face area of a cube as follows: type =, click on Cell A2, type ^2, and press Enter (note the formula bar in Fig. 4). 4. Enter the formula for cube volume in Cell C2 (same procedure, but “=, click on A2, ^3, Enter”). 5. Highlight Cells B2 and C2; plus-drag down to Row 8 (Fig. 5). Do the numbers look correct? Click on some cells in the newly filled area and notice how Excel steps the row designations as it moves down the column (it can do it for horizontal plusdrags along rows also). This is the major programming development that has led to the popularity of spreadsheets. Figure 3. Entries. Figure 4. A formula. Figure 5. Plus-dragging formulas. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com 6. Now let’s graph the Face Area versus Edge Length: select Cells A1 through B8, choose the Insert tab, and click the Scatter drop-down menu and select “Scatter with only Markers” (Fig. 6). 7. Move the graph (Excel calls it a “chart”) that appears up alongside your number table and dress it up as follows: a. Note that some Chart Layouts have appeared above. Click Layout 1 and alter each title to read Face Area for the vertical axis, Edge Length for the horizontal and Face Area vs. Edge Length for the Graph Title. b. Activate the Excel Least squares routine, called “fitting a trendline” in the program: right click any of the data markers and click Add Trendline. Choose Power and also check “Display equation on chart” and “Display R-squared value on chart.” Fig. 7 shows what the graph will look like at this point. c. The titles are explicit, so the legend is unnecessary. Click on it and press the delete button to remove it. Figure 6. Creating a scatter graph. Figure 7. A graph with a fitted curve. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com 8. Now let’s overlay the Volume vs. Edge Length curve onto the same graph (optional for 203L/205L): Make a copy of your graph by clicking on the outer white area, clicking ctrl-c (or right click, copy), and pasting the copy somewhere else (ctrl-v). If you wish, delete the trendline as in Fig. 8. a. Right click on the outer white space, choose Select Data and click the Add button. b. You can type in the cell ranges by hand in the dialog box that comes up, but it is easier to click the red, white, and blue button on the right of each space and highlight what you want to go in. Click the red, white, and blue of the bar that has appeared, and you will bounce back to the Add dialog box. Use the Edge Length column for the x’s and Volume for the y’s. c. Right-click on any volume data point and choose Format Data Series. Clicking Secondary Axis will place its scale on the right of the graph as in Fig. 8. d. Dress up your graph with two axis titles (Layout-Labels-Axis Titles), etc. Figure 8. Adding a second curve and y-axis to the graph Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 2: INTERPRETING A LINEAR GRAPH Introduction: Many experiments are repeated a number of times with one of the parameters involved varied from run to run. Often the goal is to measure the rate of change of a dependent variable, rather than a particular value. If the dependent variable can be expressed as a linear function of the independent parameter, then the slope and yintercept of an appropriate graph will give the rate of change and a particular value, respectively. An example of such an experiment in PHYS.203L/205L is the first part of Lab 20, in which weights are added to the bottom of a suspended spring (Figure 9). This experiment shows that a spring exerts a force Fs proportional to the distance stretched y = (y-yo), a relationship known as Hooke’s Law: Fs = – k(y – yo) (Eq. 1) where k is called the Hooke’s Law constant. The minus sign shows that the spring opposes any push or pull on it. In Lab 20 Fs is equal to (- Mg) and y is given by the reading on a meter stick. Masses were added to the bottom of the spring in 50-g increments giving weights in newtons of 0.49, 0.98, etc. The weight pan was used as the pointer for reading y and had a mass of 50 g, so yo could not be directly measured. For convenient graphing Equation 1 can be rewritten: -(Mg) = – ky + kyo Or (Mg) = ky – kyo (Eq. 1′) Procedure 1. On your spreadsheet note the tabs at the bottom left and double-click Sheet1. Type in “Basics,” and then click the Sheet2 tab to bring up a fresh worksheet. Change the sheet name to “Linear Fit” and fill in data as in this table. Hooke’s Law Experiment y (m) -Fs = Mg (N) 0.337 0.49 0.388 0.98 0.446 1.47 0.498 1.96 0.550 2.45 2. Highlight the cells with the numbers, and graph (Mg) versus y as in Steps 6 and 7 of the Basics section. Your Trendline this time will be Linear of course. If you are having trouble remembering what’s versus what, “y” looks like “v”, so what comes before the “v” of “versus” goes on the y (vertical) axis. Yes, this graph is confusing: the horizontal (“x”) axis is distance y, and the “y” axis is something else. 3. Click on the Equation/R2 box on the graph and highlight just the slope, that is, only the number that comes before the “x.” Copy it (control-c is a fast way to Figure 9. A spring with a weight stretching it Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com do it) and paste it (control-v) into an empty cell. Do likewise for the intercept (including the minus sign). SAVE YOUR FILE! 5. The next steps use the standard procedure for obtaining information from linear data. Write the general equation for a straight line immediately below a hand-written copy of Equation 1′ then circle matching items: (Mg) = k y + (- k yo) (Eq. 1′) y = m x + b Note the parentheses around the intercept term of Equation 1′ to emphasize that the minus sign is part of it. Equating above and below, you can create two useful new equations: slope m = k (Eq. 2) y-intercept b = -kyo (Eq. 3) 6. Solve Equation 2 for k, that is, rewrite left to right. Then substitute the value for slope m from your graph, and you have an experimental value for the Hooke’s Law constant k. Next solve Equation 3 for yo, substitute the value for intercept b from your graph and the value of k that you just found, and calculate yo. 7. Examine your linear graph for clues to finding the units of the slope and the yintercept. Use these units to find the units of k and yo. 8. Present your values of k and yo with their units neatly at the bottom of your spreadsheet. 9. R2 in Excel, like r in our lab manual and Corr. in the LoggerPro software, is a measure of how well the calculated line matches the data points. 1.00 would indicate a perfect match. State how good a match you think was made in this case? 10. Do the Homework, Further Exercises on Interpreting Linear Graphs, on the following pages. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com Eq.1 M m f M a g               , (Eq.2) M slope m g       (Eq.3) M b f        Morgan Extra Pages Homework: Graph Interpretation Exercises EXAMPLE WITH COMPLETE SOLUTION In PHYS.203L and 205L we do Lab 9 Newton’s Second Law on Atwood’s Machine using a photogate sensor (Fig. 1). The Atwood’s apparatus can slow the rate of fall enough to be measured even with primitive timing devices. In our experiment LoggerPro software automatically collects and analyzes the data giving reliable measurements of g, the acceleration of gravity. The equation governing motion for Atwood’s Machine can be written: where a is the acceleration of the masses and string, g is the acceleration of gravity, M is the total mass at both ends of the string, m is the difference between the masses, and f is the frictional force at the hub of the pulley wheel. In this exercise you are given a graph of a vs. m obtained in this experiment with the values of M and the slope and intercept (Fig. 2). The goal is to extract values for acceleration of gravity g and frictional force f from this information. To analyze the graph we write y = mx + b, the general equation for a straight line, directly under Equation 1 and match up the various parameters: Equating above and below, you can create two new equations: and y m x b M m f M a g                Figure 1. The Atwood’s Machine setup (from the LoggerPro handout). Figure 2. Graph of acceleration versus mass difference; data from a Physics I experiment. Atwood’s Machine M = 0.400 kg a = 24.4 m – 0.018 R2 = 0.998 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 0.000 0.010 0.020 0.030 0.040 0.050 0.060  m (kg) a (m/s2) Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com 2 2 9.76 / 0.400 24.4 /( ) m s kg m kg s g Mm      To handle Equation 2 it pays to consider what the units of the slope are. A slope is “the rise over the run,“ so its units must be the units of the vertical axis divided by those of the horizontal axis. In this case: Now let’s solve Equation 2 for g and substitute the values of total mass M and of the slope m from the graph: Using 9.80 m/s2 as the Baltimore accepted value for g, we can calculate the percent error: A similar process with Equation 3 leads to a value for f, the frictional force at the hub of the pulley wheel. Note that the units of intercept b are simply whatever the vertical axis units are, m/s2 in this case. Solving Equation 3 for f: EXERCISE 1 The Picket Fence experiment makes use of LoggerPro software to calculate velocities at regular time intervals as the striped plate passes through the photogate (Fig. 3). The theoretical equation is v = vi + at (Eq. 4) where vi = 0 (the fence is dropped from rest) and a = g. a. Write Equation 4 with y = mx + b under it and circle matching factors as in the Example. b. What is the experimental value of the acceleration of gravity? What is its percent error from the accepted value for Baltimore, 9.80 m/s2? c. Does the value of the y-intercept make sense? d. How well did the straight Trendline match the data? 2 / 2 kg s m kg m s   0.4% 100 9.80 9.76 9.80 100 . . . %        Acc Exp Acc Error kg m s mN kg m s f Mb 7.2 10 / 7.2 0.400 ( 0.018 / ) 3 2 2           Figure 3. Graph of speed versus time as calculated by LoggerPro as a picket fence falls freely through a photogate. Picket Fence Drop y = 9.8224x + 0.0007 R2 = 0.9997 0 2 4 6 8 10 12 0 0.2 0.4 0.6 0.8 1 1.2 t (s) v (m/s) Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 2 This is an electrical example from PHYS.204L/206L, potential difference, V, versus current, I (Fig. 4). The theoretical equation is V = IR (Eq. 5) and is known as “Ohm’s Law.” The unit symbols stand for volts, V, and Amperes, A. The factor R stands for resistance and is measured in units of ohms, symbol  (capital omega). The definition of the ohm is: V (Eq. 6) By coincidence the letter symbols for potential (a quantity ) and volts (its unit) are identical. Thus “voltage” has become the laboratory slang name for potential. a. Rearrange the Ohm’s Law equation to match y = mx + b.. b. What is the experimental resistance? c. Comment on the experimental intercept: is its value reasonable? EXERCISE 3 This graph (Fig. 5) also follows Ohm’s Law, but solved for current I. For this graph the experimenter held potential difference V constant at 15.0V and measured the current for resistances of 100, 50, 40, and 30  Solve Ohm’s Law for I and you will see that 1/R is the logical variable to use on the x axis. For units, someone once jokingly referred to a “reciprocal ohm” as a “mho,” and the name stuck. a. Rearrange Equation 5 solved for I to match y = mx + b. b. What is the experimental potential difference? c. Calculate the percent difference from the 15.0 V that the experimenter set on the power supply (the instrument used for such experiments). d. Comment on the experimental intercept: is its value reasonable? Figure 4. Graph of potential difference versus current; data from a Physics II experiment. The theoretical equation, V = IR, is known as “Ohm’s Law.” Ohm’s Law y = 0.628x – 0.0275 R2 = 0.9933 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 0.5 0.6 Current, I (A) Potential difference, V (V) Figure 5. Another application of Ohm’s Law: a graph of current versus the inverse of resistance, from a different electric circuit experiment. Current versus (1/Resistance) y = 14.727x – 0.2214 R2 = 0.9938 0 100 200 300 400 500 600 5 10 15 20 25 30 35 R-1 (millimhos) I (milliamperes) Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 4 The Atwood’s Machine experiment (see the solved example above) can be done in another way: keep mass difference m the same and vary the total mass M (Fig. 6). a. Rewrite Equation 1 and factor out (1/M). b. Equate the coefficient of (1/M) with the experimental slope and solve for acceleration of gravity g. c. Substitute the values for slope, mass difference, and frictional force and calculate the experimental of g. d. Derive the units of the slope and show that the units of g come out as they should. e. Is the value of the experimental intercept reasonable? EXERCISE 5 In the previous two exercises the reciprocal of a variable was used to make the graph come out linear. In this one the trick will be to use the square root of a variable (Fig. 7). In PHYS.203L and 205L Lab 19 The Pendulum the theoretical equation is where the period T is the time per cycle, L is the length of the string, and g is the acceleration of gravity. a. Rewrite Equation 7 with the square root of L factored out and placed at the end. b. Equate the coefficient of √L with the experimental slope and solve for acceleration of gravity g. c. Substitute the value for slope and calculate the experimental of g. d. Derive the units of the slope and show that the units of g come out as they should. e. Is the value of the experimental intercept reasonable? 2 (Eq . 7) g T   L Figure 6. Graph of acceleration versus the reciprocal of total mass; data from a another Physics I experiment. Atwood’s Machine m = 0.020 kg f = 7.2 mN y = 0.1964x – 0.0735 R2 = 0.995 0.400 0.600 0.800 1.000 2.000 2.500 3.000 3.500 4.000 4.500 5.000 1/M (1/kg) a (m/s2) Effect of Pendulum Length on Period y = 2.0523x – 0.0331 R2 = 0.999 0.400 0.800 1.200 1.600 2.000 2.400 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 L1/2 (m1/2) T (s) Figure 7. Graph of period T versus the square root of pendulum length; data from a Physics I experiment. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 6 In Exercise 5 another approach would have been to square both sides of Equation 7 and plot T2 versus L. Lab 20 directs us to use that alternative. It involves another case of periodic or harmonic motion with a similar, but more complicated, equation for the period: where T is the period of the bobbing (Fig. 8), M is the suspended mass, ms is the mass of the spring, k is a measure of stiffness called the spring constant, and C is a dimensionless factor showing how much of the spring mass is effectively bobbing. a. Square both sides of Equation 8 and rearrange it to match y = mx + b. b. Write y = mx + b under your rearranged equation and circle matching factors as in the Example. c. Write two new equations analogous to Equations 2 and 3 in the Example. Use the first of the two for calculating k and the second for finding C from the data of Fig. 9. d. A theoretical analysis has shown that for most springs C = 1/3. Find the percent error from that value. e. Derive the units of the slope and intercept; show that the units of k come out as N/m and that C is dimensionless. 2 (Eq . 8) k T M Cm s    Figure 8. In Lab 20 mass M is suspended from a spring which is set to bobbing up and down, a good approximation to simple harmonic motion (SHM), described by Equation 8. Lab 20: SHM of a Spring Mass of the spring, ms = 25.1 g y = 3.0185x + 0.0197 R2 = 0.9965 0.0000 0.2000 0.4000 0.6000 0.8000 1.0000 0 0.05 0.1 0.15 0.2 0.25 0.3 M (kg) T 2 2 Figure 9. Graph of the square of the period T2 versus suspended mass M data from a Physics I experiment. Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com EXERCISE 7 This last exercise deals with an exponential equation, and the trick is to take the logarithm of both sides. In PHYS.204L/206L we do Lab 33 The RC Time Constant with theoretical equation: where V is the potential difference at time t across a circuit element called a capacitor (the  is dropped for simplicity), Vo is V at t = 0 (try it), and  (tau) is a characteristic of the circuit called the time constant. a. Take the natural log of both sides and apply the addition rule for logarithms of a product on the right-hand side. b. Noting that the graph (Fig. 10) plots lnV versus t, arrange your equation in y = mx + b order, write y = mx + b under it, and circle the parts as in the Example. c. Write two new equations analogous to Equations 2 and 3 in the Example. Use the first of the two for calculating  and the second for finding lnVo and then Vo. d. Note that the units of lnV are the natural log of volts, lnV. As usual derive the units of the slope and interecept and use them to obtain the units of your experimental V and t. V V e (Eq. 9) t o    Figure 10. Graph of a logarithm versus time; data from Lab 33, a Physics II experiment. Discharge of a Capacitor y = -9.17E-03x + 2.00E+00 R2 = 9.98E-01 0.00 0.50 1.00 1.50 2.00 2.50

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Faculty of Science Technology and Engineering Department of Physics Senior Laboratory Faraday rotation AIM To show that optical activity is induced in a certain type of glass when it is in a magnetic field. To investigate the degree of rotation of linearly polarised light as a function of the applied magnetic field and hence determine a parameter which is characteristic of each material and known as Verdet’s constant. BACKGROUND INFORMATION A brief description of the properties and production of polarised light is given in the section labelled: Notes on polarisation. This should be read before proceeding with this experiment. Additional details may be found in the references listed at the end of this experiment. Whereas some materials, such as quartz, are naturally optically active, optical activity can be induced in others by the application of a magnetic field. For such materials, the angle through which the plane of polarisation of a linearly polarised beam is rotated () depends on the thickness of the sample (L), the strength of the magnetic field (B) and on the properties of the particular material. The latter is described by means of a parameter introduced by Verdet, which is wavelength dependent. Thus:  = V B L Lamp Polariser Solenoid Polariser Glass rod A Solenoid power supply Viewing mirror EXPERIMENTAL PROCEDURE The experimental arrangement is shown in the diagram. Unpolarised white light is produced by a hot filament and viewed using a mirror. • The light from the globe passes through two polarisers as well as the specially doped glass rod. Select one of the colour filters provided and place in the light path. Each of these filters transmits a relatively narrow band of wavelengths centred around a dominant wavelength as listed in the table. Filter No. Dominant Wavelength 98 4350 Å 50 4500 75 4900 58 5300 72 B 6060 92 6700 With the power supply for the coil switched off, (do not simply turn the potentiometer to zero: this still allows some current to flow) adjust one of the polarisers until minimum light is transmitted to the mirror. Minimum transmission can be determined visually. • Decide which polariser you will work with and do not alter the other one during the measurements. • The magnetic field is generated by a current in a solenoid (coil) placed around the glass rod. As the current in the coil is increased, the magnitude of the magnetic field will increase as shown on the calibration curve below. The degree of optical activity will also increase, resulting in some angle of rotation of the plane of polarisation. Hence you will need to rotate your chosen polariser to regain a minimum setting. 0 1 2 3 4 5 0.00 0.02 0.04 0.06 0.08 I (amps) B (tesla) Magnetic field (B) produced by current (I) in solenoid • Record the rotation angle () for coil currents of 0,1,2,3,4 and 5 amps. Avoid having the current in the coil switched on except when measurements are actually being taken as it can easily overheat. If the coil becomes too hot to touch, switch it off and wait for it to cool before proceeding. • Plot  as a function of B and, given that the length of the glass rod is 30 cm, determine Verdet’s constant for this material at the wavelength () in use. • Repeat the experiment for each of the wavelengths available using the filter set provided. • Calculate the logarithm for each V and  and tabulate the results. By plotting log V against log , determine the relationship between V and . [Hint: m log(x) = log (xm) and log(xy) = log(x) + log(y)]. • Calculate the errors involved in your determination of V. The uncertainty in a value of B may be taken as the uncertainty in reading the scale of the calibration curve) • The magnetic field direction can be reversed by reversing the direction of current flow in the coil. Describe the effect of this reversal and provide an explanation. Reference Optics Hecht.

Faculty of Science Technology and Engineering Department of Physics Senior Laboratory Faraday rotation AIM To show that optical activity is induced in a certain type of glass when it is in a magnetic field. To investigate the degree of rotation of linearly polarised light as a function of the applied magnetic field and hence determine a parameter which is characteristic of each material and known as Verdet’s constant. BACKGROUND INFORMATION A brief description of the properties and production of polarised light is given in the section labelled: Notes on polarisation. This should be read before proceeding with this experiment. Additional details may be found in the references listed at the end of this experiment. Whereas some materials, such as quartz, are naturally optically active, optical activity can be induced in others by the application of a magnetic field. For such materials, the angle through which the plane of polarisation of a linearly polarised beam is rotated () depends on the thickness of the sample (L), the strength of the magnetic field (B) and on the properties of the particular material. The latter is described by means of a parameter introduced by Verdet, which is wavelength dependent. Thus:  = V B L Lamp Polariser Solenoid Polariser Glass rod A Solenoid power supply Viewing mirror EXPERIMENTAL PROCEDURE The experimental arrangement is shown in the diagram. Unpolarised white light is produced by a hot filament and viewed using a mirror. • The light from the globe passes through two polarisers as well as the specially doped glass rod. Select one of the colour filters provided and place in the light path. Each of these filters transmits a relatively narrow band of wavelengths centred around a dominant wavelength as listed in the table. Filter No. Dominant Wavelength 98 4350 Å 50 4500 75 4900 58 5300 72 B 6060 92 6700 With the power supply for the coil switched off, (do not simply turn the potentiometer to zero: this still allows some current to flow) adjust one of the polarisers until minimum light is transmitted to the mirror. Minimum transmission can be determined visually. • Decide which polariser you will work with and do not alter the other one during the measurements. • The magnetic field is generated by a current in a solenoid (coil) placed around the glass rod. As the current in the coil is increased, the magnitude of the magnetic field will increase as shown on the calibration curve below. The degree of optical activity will also increase, resulting in some angle of rotation of the plane of polarisation. Hence you will need to rotate your chosen polariser to regain a minimum setting. 0 1 2 3 4 5 0.00 0.02 0.04 0.06 0.08 I (amps) B (tesla) Magnetic field (B) produced by current (I) in solenoid • Record the rotation angle () for coil currents of 0,1,2,3,4 and 5 amps. Avoid having the current in the coil switched on except when measurements are actually being taken as it can easily overheat. If the coil becomes too hot to touch, switch it off and wait for it to cool before proceeding. • Plot  as a function of B and, given that the length of the glass rod is 30 cm, determine Verdet’s constant for this material at the wavelength () in use. • Repeat the experiment for each of the wavelengths available using the filter set provided. • Calculate the logarithm for each V and  and tabulate the results. By plotting log V against log , determine the relationship between V and . [Hint: m log(x) = log (xm) and log(xy) = log(x) + log(y)]. • Calculate the errors involved in your determination of V. The uncertainty in a value of B may be taken as the uncertainty in reading the scale of the calibration curve) • The magnetic field direction can be reversed by reversing the direction of current flow in the coil. Describe the effect of this reversal and provide an explanation. Reference Optics Hecht.

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Lab #02 Relationship between distance & illumination As engineers, we deal with the effects of light on many projects. The first key to working with light is understanding how the light waves propagate. Once we understand light waves, we will test a manufacturers claim that lower wattage fluorescent bulbs output the same quantity of light as incandescent bulbs. This experiment is designed for you to work as a class to collect data regarding a given light source and then, working within your individual group, attempt to determine the re-lationship(s) between the measured parameter (lux) and the distance (meter) from the source. Measure and record data, in the manner described below, as a class. Work on your so-lutions as a group of 2-3. Your first task is to develop a mathematical formula, or a simple relationship that predicts the amount of lux that can be expected at a given distance from the light source. Purpose: The purpose of this assignment is to accomplish the following goals: • Gain experience collecting data in a controlled, systematic fashion. • Practice working as a group to infer relationships between variables from your collected data. • Use the data you collect to draw conclusions. In this case, to evaluate the hypothesis that the fluorescent and incandescent bulb output the same quantity of light. • Become accustomed to working in teams (note, teamwork often requires individual work as well). • Learn to balance workload across your team. (Individuals will be responsible for certain tasks, and ensure they are performed on time and to the desired quality level. • Demonstrate to me what your group’s attention to detail is, as well as your ability to construct a written explanation of work. Problem: What effect does distance have on the lux, intensity, emitted from a light source and are the 5 light bulbs producing the same intensity light? Use the rough protocol listed below and the data sheet provided to collect your data, then complete the assignment outlined below. 1. Set up a light source on one of the lab tables. 2. Using the illumination meter, measure the lux at 0.5 meter increments from the source back to 3 meters from the source. • Be sure the keep the meter perpendicular to the horizontal line from the source at all times! 3. Record your measurements on your data sheets. 4. Measurements should be taken in a random order 5. Repeat the experiment 3 times, using different people and a different order of collection and different colors. Assignment Requirements: 1. Create the appropriate graph(s) to express the data you have collected. Your report must, at the minimum, contain the following: a. An X-Y Scatter plot showing the data from both bulbs. The chart should follow all conventions taught in lecture, and display the equation for the trend-line you choose. b. A column or bar chart of your choosing showing the difference, if any, between the two bulbs. 2. Write an introduction, briefly explaining what you are accomplishing with this exper-iment. 3. Create a hierarchal outline that states, step by step, each activity that was performed to conduct the experiment and analyze the experimental data. 4. Anova analysis for data collected 5. Write a verbal explanation of what each of the charts from requirement #1 are showing. 6. Include, at the end of the document, a summary of all the tasks required to complete the assignment, including the 5 listed above, and which member or members of the group were principally responsible for completing those tasks. This should be in the form of a simple list. 7. Write at least 3 possible applications of the experiment with detailed explanation. DUE DATE: This assignment is to be completed and turned in at the beginning of your laboratory meeting during the week of 18th February Microsoft office package: Excel: Insert, page layout tab functions, Mean, standard deviation, graph functions

Lab #02 Relationship between distance & illumination As engineers, we deal with the effects of light on many projects. The first key to working with light is understanding how the light waves propagate. Once we understand light waves, we will test a manufacturers claim that lower wattage fluorescent bulbs output the same quantity of light as incandescent bulbs. This experiment is designed for you to work as a class to collect data regarding a given light source and then, working within your individual group, attempt to determine the re-lationship(s) between the measured parameter (lux) and the distance (meter) from the source. Measure and record data, in the manner described below, as a class. Work on your so-lutions as a group of 2-3. Your first task is to develop a mathematical formula, or a simple relationship that predicts the amount of lux that can be expected at a given distance from the light source. Purpose: The purpose of this assignment is to accomplish the following goals: • Gain experience collecting data in a controlled, systematic fashion. • Practice working as a group to infer relationships between variables from your collected data. • Use the data you collect to draw conclusions. In this case, to evaluate the hypothesis that the fluorescent and incandescent bulb output the same quantity of light. • Become accustomed to working in teams (note, teamwork often requires individual work as well). • Learn to balance workload across your team. (Individuals will be responsible for certain tasks, and ensure they are performed on time and to the desired quality level. • Demonstrate to me what your group’s attention to detail is, as well as your ability to construct a written explanation of work. Problem: What effect does distance have on the lux, intensity, emitted from a light source and are the 5 light bulbs producing the same intensity light? Use the rough protocol listed below and the data sheet provided to collect your data, then complete the assignment outlined below. 1. Set up a light source on one of the lab tables. 2. Using the illumination meter, measure the lux at 0.5 meter increments from the source back to 3 meters from the source. • Be sure the keep the meter perpendicular to the horizontal line from the source at all times! 3. Record your measurements on your data sheets. 4. Measurements should be taken in a random order 5. Repeat the experiment 3 times, using different people and a different order of collection and different colors. Assignment Requirements: 1. Create the appropriate graph(s) to express the data you have collected. Your report must, at the minimum, contain the following: a. An X-Y Scatter plot showing the data from both bulbs. The chart should follow all conventions taught in lecture, and display the equation for the trend-line you choose. b. A column or bar chart of your choosing showing the difference, if any, between the two bulbs. 2. Write an introduction, briefly explaining what you are accomplishing with this exper-iment. 3. Create a hierarchal outline that states, step by step, each activity that was performed to conduct the experiment and analyze the experimental data. 4. Anova analysis for data collected 5. Write a verbal explanation of what each of the charts from requirement #1 are showing. 6. Include, at the end of the document, a summary of all the tasks required to complete the assignment, including the 5 listed above, and which member or members of the group were principally responsible for completing those tasks. This should be in the form of a simple list. 7. Write at least 3 possible applications of the experiment with detailed explanation. DUE DATE: This assignment is to be completed and turned in at the beginning of your laboratory meeting during the week of 18th February Microsoft office package: Excel: Insert, page layout tab functions, Mean, standard deviation, graph functions

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Vermont Technical College Electronics I – Laboratory ELT-2051 Lab 07: Transistor Biasing Circuits and Q-point Stability Objectives: • To set an operating point for a transistor using three different bias techniques • To explore amplification of an AC signal • To use MultiSim to verify your experimental data General: In this laboratory, you will be supplied with two NPN transistors with varying ß’s. Prelab: Calculate values of Rb in Figures 1 and 2 assuming ß = 200, VCE = 6V . For Figure 3, calculate R1 and R2 so that their parallel resistance is about 20KΩ or 10% of (ß+1)RE. Also, calculate the critical frequency of the 1uF capacitor in Figure 4. Materials: • 2N3904, 2N4123 NPN TXs (1 high ß, 1 low ß) • (2) 1 k Ohm, 100 k Ohm, assorted resistors • 1uF, 10uF capacitors • Curve Tracer • DC Power Supply • Multimeter • Signal Generator • Oscilloscope • Breadboard Procedure: 1. Use the curve tracer to plot the curves for each of your transistors. From these curves, again using the curve tracer, determine the ßDC for each transistor at the IC currents of 1mA, 3mA, 6mA, and 10mA with VCE = 6V. Of course, be sure to keep track of which transistor goes with which curve. Verify that the ßDC values that you obtain are within the manufacturer’s specifications. Remember– ßDC = hFE ! 2. For each of the three circuits shown in Figures 1-3, using the R values calculated in your prelab, determine the operating points IC and VCE for each of the transistors. Be sure to table your data. In addition, plot ß vs IC for both transistors on a single graph so that the data is meaningful! What conclusions can be reached for the 3 biasing circuits? 3. Lastly – Build Figure 4 and determine the ratio (Gain) of Vout/Vin at 1KHz. Now vary the frequency of Vin to determine at what frequencies this ratio decreases to 0.707 of the value at 1KHz. 4. Use the Bode Plotter feature in MultiSim to verify your data of Part 3. Is the cut-off frequency the same as you measured in the lab? Base Bias: Parameter Calculated Value Simulated Value Measured Value VCE1 (high β) VCE2 (low β) n/a n/a |VCE1 – VCE2| 0 0 IC1 (high β) IC2 (low β) n/a n/a |IC1 – IC2| 0 0 Emitter Bias: Parameter Calculated Value Simulated Value Measured Value VCE1 (high β) VCE2 (low β) n/a n/a |VCE1 – VCE2| 0 0 IC1 (high β) IC2 (low β) n/a n/a |IC1 – IC2| 0 0 Voltage Divider Bias: Parameter Calculated Value Simulated Value Measured Value VCE1 (high β) VCE2 (low β) n/a n/a |VCE1 – VCE2| 0 0 IC1 (high β) IC2 (low β) n/a n/a |IC1 – IC2| 0 0 Laboratory Report: This lab is a semi-formal lab. Be sure to collect all data necessary to make observations and answer questions before you leave the lab. Also, you and your lab partner should discuss the results and outcomes prior to leaving. Take notes, fill in tables and include diagrams as needed. Your report should include: • Data Table • Beta Plot • MultiSim Frequency Response • Comparison of biasing schemes • Comparison of measurements vs. simulations and expectations.

Vermont Technical College Electronics I – Laboratory ELT-2051 Lab 07: Transistor Biasing Circuits and Q-point Stability Objectives: • To set an operating point for a transistor using three different bias techniques • To explore amplification of an AC signal • To use MultiSim to verify your experimental data General: In this laboratory, you will be supplied with two NPN transistors with varying ß’s. Prelab: Calculate values of Rb in Figures 1 and 2 assuming ß = 200, VCE = 6V . For Figure 3, calculate R1 and R2 so that their parallel resistance is about 20KΩ or 10% of (ß+1)RE. Also, calculate the critical frequency of the 1uF capacitor in Figure 4. Materials: • 2N3904, 2N4123 NPN TXs (1 high ß, 1 low ß) • (2) 1 k Ohm, 100 k Ohm, assorted resistors • 1uF, 10uF capacitors • Curve Tracer • DC Power Supply • Multimeter • Signal Generator • Oscilloscope • Breadboard Procedure: 1. Use the curve tracer to plot the curves for each of your transistors. From these curves, again using the curve tracer, determine the ßDC for each transistor at the IC currents of 1mA, 3mA, 6mA, and 10mA with VCE = 6V. Of course, be sure to keep track of which transistor goes with which curve. Verify that the ßDC values that you obtain are within the manufacturer’s specifications. Remember– ßDC = hFE ! 2. For each of the three circuits shown in Figures 1-3, using the R values calculated in your prelab, determine the operating points IC and VCE for each of the transistors. Be sure to table your data. In addition, plot ß vs IC for both transistors on a single graph so that the data is meaningful! What conclusions can be reached for the 3 biasing circuits? 3. Lastly – Build Figure 4 and determine the ratio (Gain) of Vout/Vin at 1KHz. Now vary the frequency of Vin to determine at what frequencies this ratio decreases to 0.707 of the value at 1KHz. 4. Use the Bode Plotter feature in MultiSim to verify your data of Part 3. Is the cut-off frequency the same as you measured in the lab? Base Bias: Parameter Calculated Value Simulated Value Measured Value VCE1 (high β) VCE2 (low β) n/a n/a |VCE1 – VCE2| 0 0 IC1 (high β) IC2 (low β) n/a n/a |IC1 – IC2| 0 0 Emitter Bias: Parameter Calculated Value Simulated Value Measured Value VCE1 (high β) VCE2 (low β) n/a n/a |VCE1 – VCE2| 0 0 IC1 (high β) IC2 (low β) n/a n/a |IC1 – IC2| 0 0 Voltage Divider Bias: Parameter Calculated Value Simulated Value Measured Value VCE1 (high β) VCE2 (low β) n/a n/a |VCE1 – VCE2| 0 0 IC1 (high β) IC2 (low β) n/a n/a |IC1 – IC2| 0 0 Laboratory Report: This lab is a semi-formal lab. Be sure to collect all data necessary to make observations and answer questions before you leave the lab. Also, you and your lab partner should discuss the results and outcomes prior to leaving. Take notes, fill in tables and include diagrams as needed. Your report should include: • Data Table • Beta Plot • MultiSim Frequency Response • Comparison of biasing schemes • Comparison of measurements vs. simulations and expectations.

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PHET ElectroMagnetism Key to this Document Instructions are in black. Experimental questions that you need to solve through experimentation with an online animation are in green highlighted. Important instructions are in red highlighted. Items that need a response from you are in yellow highlighted. Please put your answers to this activity in RED. Part I- Comparing Permanent Magnets and Electromagnets: 1. Select the simulation “Magnets and Electromagnets.” It is at this link: http://phet.colorado.edu/new/simulations/sims.php?sim=Magnets_and_Electromagnets 2. Move the compass slowly along a semicircular path above the bar magnet until you’ve put it on the opposite side of the bar magnet. Describe what happens to the compass needle. 3. Move the compass along a semicircular path below the bar magnet until you’ve put it on the opposite side of the bar magnet. Describe what happens to the compass needle. 4. What do you suppose the compass needles drawn all over the screen tell you? 5. Use page 10 in your book to look up what it looks like when scientists use a drawing to represent a magnetic field. Describe the field around a bar magnet here. 6. Put the compass to the left or right of the magnet. Click “flip polarity” and notice what happens to the compass. Using the compass needle as your observation tool, describe the effect that flipping the poles of the magnet has on the magnetic field. 7. Click on the electromagnet tab along the top of the simulation window. Place the compass on the left side of the coil so that the compass center lies along the axis of the coil. <--like this 8. Move the compass along a semicircular path above the coil until you’ve put it on the opposite side of the coil. Then do the same below the coil. Notice what happens to the compass needle. Compare this answer to the answer you got to Number 2 and 3. 9. Compare the shape of the magnetic field of a bar magnet to the magnetic field of an electromagnet. 10. Use the voltage slider to change the direction of the current and investigate the shape of the magnetic field the coil using the compass after you’ve let the compass stabilize. Summarize, the effect that the direction of current has on the shape of the magnetic field around an electrified coil of wires. 11. What happens to the current in the coil when you set the voltage of the battery to zero? 12. What happens to the magnetic field around the coil when you set the voltage of the battery to zero? Part II – Investigating relationships- No Answers are written on this document after this point. All three data tables, graphs and conclusion statements go on the Google Spreadsheet that you can download from Ms. Pogge’s website. Experimental Question #1: How does distance affect the strength of the magnetic field around an electromagnet? 1. Using the Electromagnet simulation, click on “Show Field Meter.” 2. Set the battery voltage to 10V where the positive is on the right of the battery (slide the switch all the way to the right). 3. Magnetic field strength (symbol B on the top line of the meter) is measured in gauss (G). You’ll only need to record the value on the top line of the Field Meter. 4. Position zero will be right on top of the coil. Negative number positions will be to the left and positive number positions to the right of the coil. 5. Move the field meter one compass needle to the right and record the value of B at position 1. 6. This data table below will be used to help you fill in the first spreadsheet you downloaded from Ms. Pogge’s website. You will end up with 3 data tables, 3 graphs and 3 conclusion statements in your document, one for each mini-experiment you are doing. a. NOTE: Be sure to take all of your values along the horizontal axis of the coil. You’ll know you’re on the axis because the B-y measurement of the magnetic field is zero along the axis. Compass position (no units) Magnetic Field Strength ( )<--Fill in units! -5 (5 needles to the left of coil) Don’t fill in the table here...do it on the Google Spreadsheet you downloaded -4 -3 -2 -1 0 (middle of coil) 1 2 3 4 5 (5 needles to right of coil) 7. In your Google Spreadsheet: Graph the compass position on the horizontal (x) axis and magnetic field magnitude on the vertical (y) axis. 8. Make sure to label the axes and title the graph. Share this spreadsheet with your teacher. 9. Analyze your graph to discover how the two variables are related, and report the relationship between magnetic field strength and position using 1-3 complete sentences. Experimental Question #2: How does the number of coils affect the strength of the magnetic field around an electromagnet? Design an experiment to test how field strength varies with the number of coils. Enter your data, graph your results and write your conclusion statement on the Google Spreadsheet. Experimental Question #3: How does the amount of current affect the strength of the magnetic field around an electromagnet? Design an experiment to test how field strength varies with the Current. (Recall that voltage is directly proportional to current….Ohm’s Law.) Enter your data, graph your results and write your conclusion statement on the Google Spreadsheet.

PHET ElectroMagnetism Key to this Document Instructions are in black. Experimental questions that you need to solve through experimentation with an online animation are in green highlighted. Important instructions are in red highlighted. Items that need a response from you are in yellow highlighted. Please put your answers to this activity in RED. Part I- Comparing Permanent Magnets and Electromagnets: 1. Select the simulation “Magnets and Electromagnets.” It is at this link: http://phet.colorado.edu/new/simulations/sims.php?sim=Magnets_and_Electromagnets 2. Move the compass slowly along a semicircular path above the bar magnet until you’ve put it on the opposite side of the bar magnet. Describe what happens to the compass needle. 3. Move the compass along a semicircular path below the bar magnet until you’ve put it on the opposite side of the bar magnet. Describe what happens to the compass needle. 4. What do you suppose the compass needles drawn all over the screen tell you? 5. Use page 10 in your book to look up what it looks like when scientists use a drawing to represent a magnetic field. Describe the field around a bar magnet here. 6. Put the compass to the left or right of the magnet. Click “flip polarity” and notice what happens to the compass. Using the compass needle as your observation tool, describe the effect that flipping the poles of the magnet has on the magnetic field. 7. Click on the electromagnet tab along the top of the simulation window. Place the compass on the left side of the coil so that the compass center lies along the axis of the coil. <--like this 8. Move the compass along a semicircular path above the coil until you’ve put it on the opposite side of the coil. Then do the same below the coil. Notice what happens to the compass needle. Compare this answer to the answer you got to Number 2 and 3. 9. Compare the shape of the magnetic field of a bar magnet to the magnetic field of an electromagnet. 10. Use the voltage slider to change the direction of the current and investigate the shape of the magnetic field the coil using the compass after you’ve let the compass stabilize. Summarize, the effect that the direction of current has on the shape of the magnetic field around an electrified coil of wires. 11. What happens to the current in the coil when you set the voltage of the battery to zero? 12. What happens to the magnetic field around the coil when you set the voltage of the battery to zero? Part II – Investigating relationships- No Answers are written on this document after this point. All three data tables, graphs and conclusion statements go on the Google Spreadsheet that you can download from Ms. Pogge’s website. Experimental Question #1: How does distance affect the strength of the magnetic field around an electromagnet? 1. Using the Electromagnet simulation, click on “Show Field Meter.” 2. Set the battery voltage to 10V where the positive is on the right of the battery (slide the switch all the way to the right). 3. Magnetic field strength (symbol B on the top line of the meter) is measured in gauss (G). You’ll only need to record the value on the top line of the Field Meter. 4. Position zero will be right on top of the coil. Negative number positions will be to the left and positive number positions to the right of the coil. 5. Move the field meter one compass needle to the right and record the value of B at position 1. 6. This data table below will be used to help you fill in the first spreadsheet you downloaded from Ms. Pogge’s website. You will end up with 3 data tables, 3 graphs and 3 conclusion statements in your document, one for each mini-experiment you are doing. a. NOTE: Be sure to take all of your values along the horizontal axis of the coil. You’ll know you’re on the axis because the B-y measurement of the magnetic field is zero along the axis. Compass position (no units) Magnetic Field Strength ( )<--Fill in units! -5 (5 needles to the left of coil) Don’t fill in the table here...do it on the Google Spreadsheet you downloaded -4 -3 -2 -1 0 (middle of coil) 1 2 3 4 5 (5 needles to right of coil) 7. In your Google Spreadsheet: Graph the compass position on the horizontal (x) axis and magnetic field magnitude on the vertical (y) axis. 8. Make sure to label the axes and title the graph. Share this spreadsheet with your teacher. 9. Analyze your graph to discover how the two variables are related, and report the relationship between magnetic field strength and position using 1-3 complete sentences. Experimental Question #2: How does the number of coils affect the strength of the magnetic field around an electromagnet? Design an experiment to test how field strength varies with the number of coils. Enter your data, graph your results and write your conclusion statement on the Google Spreadsheet. Experimental Question #3: How does the amount of current affect the strength of the magnetic field around an electromagnet? Design an experiment to test how field strength varies with the Current. (Recall that voltage is directly proportional to current….Ohm’s Law.) Enter your data, graph your results and write your conclusion statement on the Google Spreadsheet.

Lab #03 Studying Beam Flexion Summary: Beams are fundamental structural elements used in a variety of engineering applications and have been studied for centuries. Beams can be assembled to create large structures that carry heavy loads, such as motor vehicle traffic. Beams are also used in micro- or nano-scale accelerometers to delicately measure and detect motions that trigger the deployment of an airbag. From a technical standpoint, a beam is a structure that supports transverse load. Transverse load is load that is perpendicular to the long axis of the beam. As a result, of transverse load, beams undergo bending, in which the beam develops a curvature. As the beam bends, material fibers along the beam’s long axis are forced to stretch or contract, which in turn causes a resistance to the bending. The fibers that are the farthest away from the center of the beam are forced to stretch or contract the most and thus, material at these extremities is the most important to resist bending and deflection. This topic is studied quantitatively in Strength of Materials (CE-303). Purpose: The purpose of this assignment is to accomplish the following goals: • Develop a simple experiment to achieve a goal. • Statistically and observationally analyze your data and interpret the results. • Summarize and present your data, results and interpretations. Procedure: 1. Working as a team, develop a procedure to carefully document the amount of bending a beam under-goes as loads are placed on it (this is your experimental protocol). You must select at least two different beam styles. 2. Collect the data points your experimental protocol calls for. You should conduct at least three trials and the order of data collection within those trials should be randomized. 3. Using the provided Excel deflection calculator, calculate the “predicted” deflection for each of the trials in your protocol. 4. Please observe the following MAXIMUM test torques to avoid damaging the beams. • Width Effect Beams: Small beam: 48 in-lbs, Medium beam: 80 in-lbs, Large beam: 120 in-lbs • Depth Effect Beams: Small beam: 8 in-lbs, Medium beam: 48 in-lbs, Large beam: 160 in-lbs Report and Presentation Requirements: 1. Title Page: Should include the title of the lab experiment, groups individual names (in alphabetical order by last name), data collection date, report due date, and course name and section. 2. Introduction: Briefly explain what you are trying to accomplish with this experiment. 3. Hypothesis Development: Should clearly state the three hypotheses, with respect to distance, beam size, and calculated versus actual deflection. Be sure to include logic to support your educated guess. 4. Method: Explain each activity performed during the data collection and analysis process. Provide a list of the equipment used and its purpose. 5. Analysis and Results: (1) Using the raw data, provide a table of descriptive statistics (mean, variance, and range) for each beam at each distance. (2) Provide a data table (average across 3 trials) showing the deflection for each beam at each distance. (3) Create one or more charts demonstrating the difference, if any, between the calculated and observed deflection for each beam. (4) Use the t-Test: Paired Two Sample for Means in Excel to determine if there is a statistically significant difference between predicted (calculated) deflection and actual (observed) deflection, assuming α = 0.05. Show the results for each beam. Note: To add in the Data Analysis package (under the data tab), go to Office Button -> Excel Options -> Add-Ins -> Manage Excel Add-Ins -> GO… -> check Analysis TookPak and click OK. For each table or chart, provide a description and explanation of what is being displayed. 6. Conclusions: Restate the hypotheses and explain whether or not the educated guess was correct. Include limitations of the experiment (in other words, describe other factors that would make the experiment better or possible errors associated with the experiment). Provide suggestions for future research. 7. Last Page: Include, at the end of the document, a summary of all the tasks required to complete the assignment, and which member or members of the group were principally responsible for completing those tasks. This should be in the form of a simple list. 8. Presentation: Summarize the report, excluding the last page. Due Date: This assignment is to be completed and turned in at the beginning of your laboratory meeting during the week of 11th March. Microsoft office package: Excel: Data tab functions, round, drag-drop, $-sign functions, Beginning of analysis toolpak-t-tests

Lab #03 Studying Beam Flexion Summary: Beams are fundamental structural elements used in a variety of engineering applications and have been studied for centuries. Beams can be assembled to create large structures that carry heavy loads, such as motor vehicle traffic. Beams are also used in micro- or nano-scale accelerometers to delicately measure and detect motions that trigger the deployment of an airbag. From a technical standpoint, a beam is a structure that supports transverse load. Transverse load is load that is perpendicular to the long axis of the beam. As a result, of transverse load, beams undergo bending, in which the beam develops a curvature. As the beam bends, material fibers along the beam’s long axis are forced to stretch or contract, which in turn causes a resistance to the bending. The fibers that are the farthest away from the center of the beam are forced to stretch or contract the most and thus, material at these extremities is the most important to resist bending and deflection. This topic is studied quantitatively in Strength of Materials (CE-303). Purpose: The purpose of this assignment is to accomplish the following goals: • Develop a simple experiment to achieve a goal. • Statistically and observationally analyze your data and interpret the results. • Summarize and present your data, results and interpretations. Procedure: 1. Working as a team, develop a procedure to carefully document the amount of bending a beam under-goes as loads are placed on it (this is your experimental protocol). You must select at least two different beam styles. 2. Collect the data points your experimental protocol calls for. You should conduct at least three trials and the order of data collection within those trials should be randomized. 3. Using the provided Excel deflection calculator, calculate the “predicted” deflection for each of the trials in your protocol. 4. Please observe the following MAXIMUM test torques to avoid damaging the beams. • Width Effect Beams: Small beam: 48 in-lbs, Medium beam: 80 in-lbs, Large beam: 120 in-lbs • Depth Effect Beams: Small beam: 8 in-lbs, Medium beam: 48 in-lbs, Large beam: 160 in-lbs Report and Presentation Requirements: 1. Title Page: Should include the title of the lab experiment, groups individual names (in alphabetical order by last name), data collection date, report due date, and course name and section. 2. Introduction: Briefly explain what you are trying to accomplish with this experiment. 3. Hypothesis Development: Should clearly state the three hypotheses, with respect to distance, beam size, and calculated versus actual deflection. Be sure to include logic to support your educated guess. 4. Method: Explain each activity performed during the data collection and analysis process. Provide a list of the equipment used and its purpose. 5. Analysis and Results: (1) Using the raw data, provide a table of descriptive statistics (mean, variance, and range) for each beam at each distance. (2) Provide a data table (average across 3 trials) showing the deflection for each beam at each distance. (3) Create one or more charts demonstrating the difference, if any, between the calculated and observed deflection for each beam. (4) Use the t-Test: Paired Two Sample for Means in Excel to determine if there is a statistically significant difference between predicted (calculated) deflection and actual (observed) deflection, assuming α = 0.05. Show the results for each beam. Note: To add in the Data Analysis package (under the data tab), go to Office Button -> Excel Options -> Add-Ins -> Manage Excel Add-Ins -> GO… -> check Analysis TookPak and click OK. For each table or chart, provide a description and explanation of what is being displayed. 6. Conclusions: Restate the hypotheses and explain whether or not the educated guess was correct. Include limitations of the experiment (in other words, describe other factors that would make the experiment better or possible errors associated with the experiment). Provide suggestions for future research. 7. Last Page: Include, at the end of the document, a summary of all the tasks required to complete the assignment, and which member or members of the group were principally responsible for completing those tasks. This should be in the form of a simple list. 8. Presentation: Summarize the report, excluding the last page. Due Date: This assignment is to be completed and turned in at the beginning of your laboratory meeting during the week of 11th March. Microsoft office package: Excel: Data tab functions, round, drag-drop, $-sign functions, Beginning of analysis toolpak-t-tests

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