BI 102 Lab 1 Writing Assignment How did the different concentrations of sucrose impact osmotic rate? This assignment requires you to evaluate a hypothesis and communicate the results of your experiment on the rate of osmosis into sucrose solutions of varying concentrations. The questions below are meant to guide you to reporting the key findings of your experiment and help you think through how to explain the findings and draw conclusions from them in a scientific manner. ASSIGNMENT: Please respond to the following questions to complete your laboratory write up. For this assignment you will only focus on the osmosis of water into sucrose concentrations of varying concentration. Make sure that your write up is accurate, and clearly written so that it is easily readable. A grading rubric is provided on the second page of this assignment. To earn full points on your write up, you must provide answers that align to the “meets” column of your grading rubric as well as meeting all “Quality of Writing and Mechanics” elements described in the rubric. There are also some tips on pages 3-4 of this assignment to help you succeed. FORMAT: • Type your responses, using 1.5 or double spacing. • Include the section headings (Hypothesis, Results, Analysis) and question number (example: 1, 2, 3, etc) in your answers but do not rewrite the question. • Graphs may be made with a computer program (example: Microsoft excel, Mac numbers, etc) or may be neatly produced with a ruler on graphing paper. • Print out the cover sheet on page 2 of this assignment, read and sign the academic honesty statement, and submit it with your write up. Your instructor WILL NOT accept a write up without the signed cover sheet. DUE DATE: Your write up is due at the beginning of class next week. Late assignments will have 1 point deducted per day up to 5 days, at which point the assignment will be assigned 0 points. Hypothesis and Prediction – Part 1 of Rubric 1. What did you think was going to happen in this experiment and why? You may find it helpful to state your answers to these questions as an “if-then” hypothesis-prediction. Be sure you have included a biological rationale that explains WHY you made this hypothesis/prediction. (You worked on this in question 2 on page 10 of this lab activity) Results – Part 2 of Rubric 2. How did the different concentrations of sucrose impact osmotic rate? Answer this question by creating a line graph that shows the results of your experiment. If you need assistance building a graph, there is a Guide to Graphing resource available on your Moodle lab course site. Analysis- Part 3 of Rubric 3. Explain why you think that the results shown in your graph support or refute your hypothesis (remember we never “prove” anything in science). Consider all your data and the overall data pattern as you answer this question. Don’t ignore unusual data that may not seem to fit into a specific patterns (“outliers”). Explain what you think might be behind these unusual data points. 4. What is the biological significance of your results? What biological concepts explain completely why these events happened in the experiment? How do these results help you understand the biology of the cell and how materials move back and forth across the cell membrane? (A hint: refer back to questions 1A-1F on page 10 of this lab activity). Think about giving a specific example. References- Mechanics Checklist 5. Provide at least one full citation (make sure you include an in-text citation that pinpoints where you used this resource) for a resource you made use of in performing the experiment, understanding the concepts and writing this assignment. (Perhaps your lab manual? Your textbook? A website?) If you used more than one resource, you need to cite each one! If you need help with citations, a Guide to Citing References is available on your Moodle lab course site. Please print out and submit this cover sheet with your lab writeup! Lab Writeup Assignment (1) Assessment Rubric-­‐ 10 points total Name: ________________________________________ Element Misses (1 point) Approaches (2 points) Meets (3 points) Hypothesis Clarity/Specificity Testability Rationale ___Hypothesis is unclear and hardto- understand ___Hypothesis is not testable ___No biological rationale for hypothesis or rationale is fully inaccurate ___Hypothesis included is clearly stated, but not specific or lacks specific details __Hypothesis is testable, but not in a feasible way in this lab ___Some foundation for hypothesis, but based in part on biological inaccuracy ___Hypothesis included is clearly stated and very specific ___Hypothesis is testable and could be tested within lab parameters ___Rationale for hypothesis is grounded in accurate biological information Graph Title Axes Variables Key Graph clarity Data accuracy ___Graph lacks a title ___Axes are not labeled ___Variables not addressed in graph ___No key or way to tell data points apart ___Graph is hard to read and comparisons cannot be made: Inappropriate graph type or use of scale ___Data graphed is inaccurate or does not relate to experiment ___Graph has a title that is not very descriptive ___Axes are either unlabeled, or units are unclear or wrong ___Variables addressed in graph, but not on correct axes ___Key included, but is hard to understand ___Graph is somewhat readable, comparisons can be made with difficulty: Appropriate graph type, but not scaled well ___Data graphed is partially accurate; some data is missing ___Graph has a concise, descriptive title ___Axes are labeled, including clarification of units used ___Variables on correct axes ___A clear, easy-to-use key to data points is included ___Graph is clearly readable and comparisons between treatments are easy to make: Graph type and scale are appropriate to data ___Data graphed is accurate and includes all relevant data, including controls (if needed) Analysis Hypothesis Scientific language Data addressed Explanation ___Hypothesis is not addressed ___Hypothesis is described using language like proven, true, or right ___No explanations for data patterns observed in graph or data does not support conclusions. ___No biological explanation for data trends or explanations are completely inaccurate ___Hypothesis is mentioned, but not linked well to data ___Hypothesis is not consistently described as supported or refuted ___Some data considered in conclusions but other data is ignored. Any unusual “outliers” are ignored ___Explanations include minimal or some inaccurate biological concepts ___Hypothesis is evaluated based upon data ___Hypothesis is consistently described as supported or refuted ___All data collected is considered and addressed by conclusions, including presence of outliers, ___Explanations include relevant and accurate biological concepts Quality of Writing and Mechanics: Worth 1 point. Writeup should meet all of the following criteria! Yes No ☐ ☐ Write up includes your name, the date, and your lab section ☐ ☐ Write up is free from spelling and grammatical errors (make sure you proofread!!) ☐ ☐ Write up is clear and easy-to-understand ☐ ☐ Write up includes full citation for at least one reference with corresponding in-text citation ☐ ☐ All portions of write up are clearly labeled, and question numbers are included Plagiarism refers to the use of original work, ideas, or text that are not your own. This includes cut-and-paste from websites, copying directly from texts, and copying the work of others, including fellow students. Telling someone your answers to the questions (including telling someone how to make their graph, question #2), or asking for the answers to any question, is cheating. (Asking someone how to make the graph for this assignment is NOT the same as asking for help learning excel or some other software). All forms of cheating, including plagiarism and copying of work will result in an immediate zero for the exam, quiz, or assignment. In the case of copying, all parties involved in the unethical behavior will earn zeros. Cheating students will be referred to the Student Conduct Committee for further action. You also have the right to appeal to the Student Conduct Committee. I have read and understand the plagiarism statement. ____________________________________________________ Signature Guidelines for Good Quality Scientific Reports Hypothesis and Prediction: The hypothesis is a tentative explanation for the phenomenon. Remember that: • A good hypothesis and prediction is testable (and should be testable under the conditions of our lab environment; For example, if your hypothesis requires shooting a rocket into space, then its not really testable under our laboratory conditions). • Your explanation can be ruled out through testing, or falsified. • A good hypothesis and prediction is detailed and specific in what it is testing. • A good hypothesis provides a rationale or explanation for why you think your prediction is reasonable and this rationale is based on what we know about biology. • A good prediction is specific and can be tested with a specific experiment. Examples*: I think that diet soda will float and regular soda will sink. {This hypothesis misses the goal. It is not specific as we don’t know where the sodas are floating and sinking, and it does not provide any explanation to explain why the hypothesis makes sense} Because diet soda does not contain sugar and regular soda does, the diet soda will float in a bucket of water, while regular soda will sink. {This hypothesis approaches the goal. It is more specific about the conditions, and it provides a partial explanation about why the hypothesis makes sense, but the connection between sugar and sinking is unclear} If diet soda does not contain sugar, then its density (mass/volume) is lower than that of regular soda which does contain sugar, and so diet soda will float in a bucket of water while regular soda sinks. {This hypothesis meets the goal. It is specific and the rationale- sugar affects density and density is what determines floating or sinking in water- is clearly articulated} *Note that these examples are for different experiments and investigations and NOT about your osmosis lab. They are provided only to help you think about what you need to include in your write up. Graph: The graph is a visual representation of the data you gathered while testing your hypothesis. Remember that: • A graph needs a concise title that clearly describes the data that it is showing. • Data must be put on the correct axes of the graph. In general, the data you collected (representing what you are trying to find out about) goes on the vertical (Y) axis. The supporting data that that describes how, when or under what conditions you collected your data goes on the horizontal (X) axis. (For this reason time nearly always goes on the X-axis). • Axes must be labeled, including the units in which data were recorded • Data points should be clearly marked and identified; a key is helpful if more than one group of data is included in the graph. • The scale of a graph is important. It should be consistent (there should be no change in the units or increments on a single axis) and appropriate to the data you collected Examples: {This graph misses the goal. There is no title, nor is there a key to help distinguish what the data points mean. The scale is too large- from 0 to 100 with an increment of 50, when the maximum number in the graph is 25- and makes it hard to interpret this graph. The x-axis is labeled, but without units (the months) and the y-axis has units, but the label is incomplete- number of what?} {This graph meets the goal. There is a descriptive title, and all of the axes are clearly labeled with units. There is a key so that we can distinguish what each set of data points represent. The dependent variable (number of individuals) is correctly placed on the y-axis with the independent variable of time placed on the x-axis. The scale of 0-30 is appropriate to the data, with each line on the x-axis representing an increment of 5.} 0 50 100 Number Month 0 5 10 15 20 25 30 March April May June July Number of individuals Month (2011) Population size of three different madtom catiCish in the Marais de Cygnes River in Spring/Summer 2011 Brindled madtom Neosho madtom Slender madtom Analysis: You need to evaluate your hypothesis based on the data patterns shown by your graph. Remember that: • You use data to determine support or refute your hypothesis. It is only possible to support a hypothesis, not to “prove” one (that would require testing every possible permutation and combination of factors). Your evaluation of your hypothesis should not be contradicted by the pattern shown by your data. • Refer back to the prediction you made as part of your hypothesis and use your data to justify your decision to support or refute your hypothesis. • In the “if” part of your hypothesis you should have provided a rationale, or explanation for the prediction you made in your hypothesis (“then” part of hypothesis”). Use this to help you explain why you think you observed the specific pattern of data revealed in your graph. • You should consider all of the data you collected in examining the support (or lack of support for your hypothesis). If there are unusual data points or “outliers” that don’t seem to fit the general pattern in your graph, explain what you think those mean. Examples: I was right. Diet Pepsi floated and so did Apricot Nectar. Regular Pepsi sank. Obviously the regular Pepsi was heavier. This helps us understand the concept of density, which is a really important one. {This analysis misses the goal. The hypothesis isn’t actually mentioned and the data is only briefly described. There is no explanation of the importance of the Apricot Nectar results. Finally, there is no connection to how these results help understand density or why it is biologically important} I hypothesized that diet soda would float, and all three cans of diet Pepsi did float while the regular Pepsi sank. This supports my hypothesis. Both types of Pepsi were 8.5 fluid ounces in volume, but the regular Pepsi also contained 16 grams of sugar. This means that the regular Pepsi had 16 more grams of mass provided by the sugar in the same amount of volume. This would lead to an increase in density, which explains why the regular soda cans sank. When we put in a can of Apricot Nectar, which had 19 grams of sugar, it floated. This was unexpected, but I think it is explained by the fact that an Apricot Nectar can had a volume of 7 fluid ounces, but the dimensions of the can are the same as that of a Pepsi can. A same-sized can with less liquid probably has an air space that helped it float. The results of this experiment help us understand how the air bladder of a fish, which creates an air space inside the fish, helps it float in the water and also how seaweeds and other living things with air spaces or other factors that decrease their density keep from sinking to the bottom of the water. {This analysis meets the goal. It clearly ties the hypothesis to the results and outlines what they mean. It describes how the results support the hypothesis, but also explains a possible reason behind the unusual results of the Apricot Nectar. Finally, there is a link to how this experiment helps us understand biology}

BI 102 Lab 1 Writing Assignment How did the different concentrations of sucrose impact osmotic rate? This assignment requires you to evaluate a hypothesis and communicate the results of your experiment on the rate of osmosis into sucrose solutions of varying concentrations. The questions below are meant to guide you to reporting the key findings of your experiment and help you think through how to explain the findings and draw conclusions from them in a scientific manner. ASSIGNMENT: Please respond to the following questions to complete your laboratory write up. For this assignment you will only focus on the osmosis of water into sucrose concentrations of varying concentration. Make sure that your write up is accurate, and clearly written so that it is easily readable. A grading rubric is provided on the second page of this assignment. To earn full points on your write up, you must provide answers that align to the “meets” column of your grading rubric as well as meeting all “Quality of Writing and Mechanics” elements described in the rubric. There are also some tips on pages 3-4 of this assignment to help you succeed. FORMAT: • Type your responses, using 1.5 or double spacing. • Include the section headings (Hypothesis, Results, Analysis) and question number (example: 1, 2, 3, etc) in your answers but do not rewrite the question. • Graphs may be made with a computer program (example: Microsoft excel, Mac numbers, etc) or may be neatly produced with a ruler on graphing paper. • Print out the cover sheet on page 2 of this assignment, read and sign the academic honesty statement, and submit it with your write up. Your instructor WILL NOT accept a write up without the signed cover sheet. DUE DATE: Your write up is due at the beginning of class next week. Late assignments will have 1 point deducted per day up to 5 days, at which point the assignment will be assigned 0 points. Hypothesis and Prediction – Part 1 of Rubric 1. What did you think was going to happen in this experiment and why? You may find it helpful to state your answers to these questions as an “if-then” hypothesis-prediction. Be sure you have included a biological rationale that explains WHY you made this hypothesis/prediction. (You worked on this in question 2 on page 10 of this lab activity) Results – Part 2 of Rubric 2. How did the different concentrations of sucrose impact osmotic rate? Answer this question by creating a line graph that shows the results of your experiment. If you need assistance building a graph, there is a Guide to Graphing resource available on your Moodle lab course site. Analysis- Part 3 of Rubric 3. Explain why you think that the results shown in your graph support or refute your hypothesis (remember we never “prove” anything in science). Consider all your data and the overall data pattern as you answer this question. Don’t ignore unusual data that may not seem to fit into a specific patterns (“outliers”). Explain what you think might be behind these unusual data points. 4. What is the biological significance of your results? What biological concepts explain completely why these events happened in the experiment? How do these results help you understand the biology of the cell and how materials move back and forth across the cell membrane? (A hint: refer back to questions 1A-1F on page 10 of this lab activity). Think about giving a specific example. References- Mechanics Checklist 5. Provide at least one full citation (make sure you include an in-text citation that pinpoints where you used this resource) for a resource you made use of in performing the experiment, understanding the concepts and writing this assignment. (Perhaps your lab manual? Your textbook? A website?) If you used more than one resource, you need to cite each one! If you need help with citations, a Guide to Citing References is available on your Moodle lab course site. Please print out and submit this cover sheet with your lab writeup! Lab Writeup Assignment (1) Assessment Rubric-­‐ 10 points total Name: ________________________________________ Element Misses (1 point) Approaches (2 points) Meets (3 points) Hypothesis Clarity/Specificity Testability Rationale ___Hypothesis is unclear and hardto- understand ___Hypothesis is not testable ___No biological rationale for hypothesis or rationale is fully inaccurate ___Hypothesis included is clearly stated, but not specific or lacks specific details __Hypothesis is testable, but not in a feasible way in this lab ___Some foundation for hypothesis, but based in part on biological inaccuracy ___Hypothesis included is clearly stated and very specific ___Hypothesis is testable and could be tested within lab parameters ___Rationale for hypothesis is grounded in accurate biological information Graph Title Axes Variables Key Graph clarity Data accuracy ___Graph lacks a title ___Axes are not labeled ___Variables not addressed in graph ___No key or way to tell data points apart ___Graph is hard to read and comparisons cannot be made: Inappropriate graph type or use of scale ___Data graphed is inaccurate or does not relate to experiment ___Graph has a title that is not very descriptive ___Axes are either unlabeled, or units are unclear or wrong ___Variables addressed in graph, but not on correct axes ___Key included, but is hard to understand ___Graph is somewhat readable, comparisons can be made with difficulty: Appropriate graph type, but not scaled well ___Data graphed is partially accurate; some data is missing ___Graph has a concise, descriptive title ___Axes are labeled, including clarification of units used ___Variables on correct axes ___A clear, easy-to-use key to data points is included ___Graph is clearly readable and comparisons between treatments are easy to make: Graph type and scale are appropriate to data ___Data graphed is accurate and includes all relevant data, including controls (if needed) Analysis Hypothesis Scientific language Data addressed Explanation ___Hypothesis is not addressed ___Hypothesis is described using language like proven, true, or right ___No explanations for data patterns observed in graph or data does not support conclusions. ___No biological explanation for data trends or explanations are completely inaccurate ___Hypothesis is mentioned, but not linked well to data ___Hypothesis is not consistently described as supported or refuted ___Some data considered in conclusions but other data is ignored. Any unusual “outliers” are ignored ___Explanations include minimal or some inaccurate biological concepts ___Hypothesis is evaluated based upon data ___Hypothesis is consistently described as supported or refuted ___All data collected is considered and addressed by conclusions, including presence of outliers, ___Explanations include relevant and accurate biological concepts Quality of Writing and Mechanics: Worth 1 point. Writeup should meet all of the following criteria! Yes No ☐ ☐ Write up includes your name, the date, and your lab section ☐ ☐ Write up is free from spelling and grammatical errors (make sure you proofread!!) ☐ ☐ Write up is clear and easy-to-understand ☐ ☐ Write up includes full citation for at least one reference with corresponding in-text citation ☐ ☐ All portions of write up are clearly labeled, and question numbers are included Plagiarism refers to the use of original work, ideas, or text that are not your own. This includes cut-and-paste from websites, copying directly from texts, and copying the work of others, including fellow students. Telling someone your answers to the questions (including telling someone how to make their graph, question #2), or asking for the answers to any question, is cheating. (Asking someone how to make the graph for this assignment is NOT the same as asking for help learning excel or some other software). All forms of cheating, including plagiarism and copying of work will result in an immediate zero for the exam, quiz, or assignment. In the case of copying, all parties involved in the unethical behavior will earn zeros. Cheating students will be referred to the Student Conduct Committee for further action. You also have the right to appeal to the Student Conduct Committee. I have read and understand the plagiarism statement. ____________________________________________________ Signature Guidelines for Good Quality Scientific Reports Hypothesis and Prediction: The hypothesis is a tentative explanation for the phenomenon. Remember that: • A good hypothesis and prediction is testable (and should be testable under the conditions of our lab environment; For example, if your hypothesis requires shooting a rocket into space, then its not really testable under our laboratory conditions). • Your explanation can be ruled out through testing, or falsified. • A good hypothesis and prediction is detailed and specific in what it is testing. • A good hypothesis provides a rationale or explanation for why you think your prediction is reasonable and this rationale is based on what we know about biology. • A good prediction is specific and can be tested with a specific experiment. Examples*: I think that diet soda will float and regular soda will sink. {This hypothesis misses the goal. It is not specific as we don’t know where the sodas are floating and sinking, and it does not provide any explanation to explain why the hypothesis makes sense} Because diet soda does not contain sugar and regular soda does, the diet soda will float in a bucket of water, while regular soda will sink. {This hypothesis approaches the goal. It is more specific about the conditions, and it provides a partial explanation about why the hypothesis makes sense, but the connection between sugar and sinking is unclear} If diet soda does not contain sugar, then its density (mass/volume) is lower than that of regular soda which does contain sugar, and so diet soda will float in a bucket of water while regular soda sinks. {This hypothesis meets the goal. It is specific and the rationale- sugar affects density and density is what determines floating or sinking in water- is clearly articulated} *Note that these examples are for different experiments and investigations and NOT about your osmosis lab. They are provided only to help you think about what you need to include in your write up. Graph: The graph is a visual representation of the data you gathered while testing your hypothesis. Remember that: • A graph needs a concise title that clearly describes the data that it is showing. • Data must be put on the correct axes of the graph. In general, the data you collected (representing what you are trying to find out about) goes on the vertical (Y) axis. The supporting data that that describes how, when or under what conditions you collected your data goes on the horizontal (X) axis. (For this reason time nearly always goes on the X-axis). • Axes must be labeled, including the units in which data were recorded • Data points should be clearly marked and identified; a key is helpful if more than one group of data is included in the graph. • The scale of a graph is important. It should be consistent (there should be no change in the units or increments on a single axis) and appropriate to the data you collected Examples: {This graph misses the goal. There is no title, nor is there a key to help distinguish what the data points mean. The scale is too large- from 0 to 100 with an increment of 50, when the maximum number in the graph is 25- and makes it hard to interpret this graph. The x-axis is labeled, but without units (the months) and the y-axis has units, but the label is incomplete- number of what?} {This graph meets the goal. There is a descriptive title, and all of the axes are clearly labeled with units. There is a key so that we can distinguish what each set of data points represent. The dependent variable (number of individuals) is correctly placed on the y-axis with the independent variable of time placed on the x-axis. The scale of 0-30 is appropriate to the data, with each line on the x-axis representing an increment of 5.} 0 50 100 Number Month 0 5 10 15 20 25 30 March April May June July Number of individuals Month (2011) Population size of three different madtom catiCish in the Marais de Cygnes River in Spring/Summer 2011 Brindled madtom Neosho madtom Slender madtom Analysis: You need to evaluate your hypothesis based on the data patterns shown by your graph. Remember that: • You use data to determine support or refute your hypothesis. It is only possible to support a hypothesis, not to “prove” one (that would require testing every possible permutation and combination of factors). Your evaluation of your hypothesis should not be contradicted by the pattern shown by your data. • Refer back to the prediction you made as part of your hypothesis and use your data to justify your decision to support or refute your hypothesis. • In the “if” part of your hypothesis you should have provided a rationale, or explanation for the prediction you made in your hypothesis (“then” part of hypothesis”). Use this to help you explain why you think you observed the specific pattern of data revealed in your graph. • You should consider all of the data you collected in examining the support (or lack of support for your hypothesis). If there are unusual data points or “outliers” that don’t seem to fit the general pattern in your graph, explain what you think those mean. Examples: I was right. Diet Pepsi floated and so did Apricot Nectar. Regular Pepsi sank. Obviously the regular Pepsi was heavier. This helps us understand the concept of density, which is a really important one. {This analysis misses the goal. The hypothesis isn’t actually mentioned and the data is only briefly described. There is no explanation of the importance of the Apricot Nectar results. Finally, there is no connection to how these results help understand density or why it is biologically important} I hypothesized that diet soda would float, and all three cans of diet Pepsi did float while the regular Pepsi sank. This supports my hypothesis. Both types of Pepsi were 8.5 fluid ounces in volume, but the regular Pepsi also contained 16 grams of sugar. This means that the regular Pepsi had 16 more grams of mass provided by the sugar in the same amount of volume. This would lead to an increase in density, which explains why the regular soda cans sank. When we put in a can of Apricot Nectar, which had 19 grams of sugar, it floated. This was unexpected, but I think it is explained by the fact that an Apricot Nectar can had a volume of 7 fluid ounces, but the dimensions of the can are the same as that of a Pepsi can. A same-sized can with less liquid probably has an air space that helped it float. The results of this experiment help us understand how the air bladder of a fish, which creates an air space inside the fish, helps it float in the water and also how seaweeds and other living things with air spaces or other factors that decrease their density keep from sinking to the bottom of the water. {This analysis meets the goal. It clearly ties the hypothesis to the results and outlines what they mean. It describes how the results support the hypothesis, but also explains a possible reason behind the unusual results of the Apricot Nectar. Finally, there is a link to how this experiment helps us understand biology}

info@checkyourstudy.com Whatsapp +919911743277
Take Home Exam 3: Special Note Before Starting the Exam: If you scan your solutions to the exam and save it as a pdf or image file and put it on dropbox and I can not read it or open it, you will not receive credit for the exam. Furthermore, if you write the solutions up in word, latex ect. and give me a print out, which does not include all the pages you will not get credit for the missing pages. Also if your folder on dropbox is not clearly labeled and I can not find your exam then you will not get credit for the exam. Finally, please make sure you put your name on the exam!! Math 2100 Exam 3, Out of Class, Due by December 8th, 2015 at 5:00 pm. Name: Problem 1. (15 points) A random variable is said to have the (standard) Cauchy distribution if its PDF is given by f (x) = 1 π 1 1+ x2 , −∞< x <∞ This problem uses computer simulations to demonstrate that a) samples from this distribution often have extreme outliers (a consequence of the heavy tails of the distribution), and b) the sample mean is prone to the same type of outliers. Below is a graph of the pdf a) (5 points) The R commands x=rcauchy(500); summary(x) generate a random sample of size 500 from the Cauchy distribution and display the sample’s five number summary; Report the five number summary and the interquartile range, and comment on whether or not the smallest and largest numbers generated from this sample of 500 are outliers. Repeat this 10 times. b) (5 points) The R commands m=matrix(rcauchy(50000), nrow=500); xb=apply(m,1,mean);summary(xb) generate the matrix m that has 500 rows, each of which is a sample of size n=100 from the Cauchy distribution, compute the 500 sample means and store them in xb. and display the five number summary xb. Repeat these commands 10 times, and report the 10 sets of five number summaries. Compare with the 10 sets of five number summaries from part (a), and comment on whether or not the distribution of the averages seems to be more prone to extreme outliers as that of the individual observations. c) (5 points) Why does this happen? (hint: try to calculate E(X) and V(X) for this distribution) and does the LLN and CLT apply for samples from a Cauchy distribution? Hint: E(X) is undefined for this distribution unless you use the Cauchy Principle Value as such for the mean lim a→∞ xf (x)dx −a a∫ In addition x2 1+ x2 dx = x2 +1−1 1+ x2 dx = 1− 1 1+ x2 " # $ % & ' ∫ ∫ ∫ dx 1 1+ x2 dx = tan−1 ∫ x +C Problem 2. (5 points) A marketing expert for a pasta-making company believes that 40% of pasta lovers prefer lasagna. If 9 out of 20 pasta lovers choose lasagna over other pastas, what can be concluded about the expert's claim? Use a 0.05 level of significance. Problem 3. (10 points) A coin is tossed 20 times, resulting in 5 heads. Is this sufficient evidence to reject the hypothesis that the coin is balanced in favor of the alternative that heads occur less than 50% of the time (essentially is this significant evidence to claim that the coin is unbalanced in favor of tails)? Use a 0.05 level of significance. Problem 4. (25 points) Since the chemical benzene may cause cancer, the federal government has set the maximum allowable benzene concentration in the workplace at 1 part per million (1 ppm) Suppose that a steel manufacturing plant is under investigation for possible violations regarding benzene level. The Occupational Safety and Health Administration (OSHA) will analyze 14 air samples over a one-month period. Assume normality of the population from which the samples were drawn. a) (3 points) What is an appropriate null hypothesis for this scenario? (Give this in symbols) b) (3 points) What is an appropriate alternative hypothesis for this scenario? (Give this in symbols) c) (3 points) What kind of hypothesis test is this: left-tailed, right-tailed or two-tailed? Explain how you picked your answer. d) (3 points) Is this a one-sample t-test or a one-sample test using a normal distribution? Explain how you picked your answer. e) (4 points) If the test using this sample of size 14 is to be done at the 1% significance level, calculate the critical value(s) and describe the rejection region(s) for the test statistic. Show your work. f) (5 points) OHSA finds the following for their sample of size 14: a mean benzene level of 1.51 ppm and a standard deviation of 1.415 ppm. What should be concluded at the 1% significance level? Support your answer with calculation(s) and reasoning. g) (4 points) Calculate the p-value for this test and verify that this answer would lead to the same conclusion you made in part f. Problem 5. (15 points) A normally distributed random variable Y possesses a mean of μ = 20 and a standard deviation of σ = 5. A random sample of n = 31 observations is to be selected. Let X be the sample average. (X in this problem is really x _ ) a)(5 points) Describe the sampling distribution of X (i.e. describe the distribution of X and give μx, σx ) b) (5 points) Find the z-score of x = 22 c) (5 points) Find P(X ≥ 22) = Problem 6. (10 points) A restaurants receipts show that the cost of customers' dinners has a distribution with a mean of $54 and a standard deviation of $18. What is the probability that the next 100 customers will spend a total of at least $5800 on dinner? Problem 7. (10 points) The operations manager of a large production plant would like to estimate the mean amount of time a worker takes to assemble a new electronic component. Assume that the standard deviation of this assembly time is 3.6 minutes and is normally distributed. a) (3 points) After observing 120 workers assembling similar devices, the manager noticed that their average time was 16.2 minutes. Construct a 92% confidence interval for the mean assembly time. b) (2 points) How many workers should be involved in this study in order to have the mean assembly time estimated up to ± 15 seconds with 92% confidence? c) (5 points) Construct a 92% confidence interval if instead of observing 120 workers assembling similar devices, rather the manager observes 25 workers and notice their average time was 16.2 minutes with a standard deviation of 4.0 minutes. Problem 8. (10 points): A manufacturer of candy must monitor the temperature at which the candies are baked. Too much variation will cause inconsistency in the taste of the candy. Past records show that the standard deviation of the temperature has been 1.2oF . A random sample of 30 batches of candy is selected, and the sample standard deviation of the temperature is 2.1oF . a. (5 points) At the 0.05 level of significance, is there evidence that the population standard deviation has increased above 1.2oF ? b. (3 points) What assumption do you need to make in order to perform this test? c. (2 points) Compute the p-value in (a) and interpret its meaning.

Take Home Exam 3: Special Note Before Starting the Exam: If you scan your solutions to the exam and save it as a pdf or image file and put it on dropbox and I can not read it or open it, you will not receive credit for the exam. Furthermore, if you write the solutions up in word, latex ect. and give me a print out, which does not include all the pages you will not get credit for the missing pages. Also if your folder on dropbox is not clearly labeled and I can not find your exam then you will not get credit for the exam. Finally, please make sure you put your name on the exam!! Math 2100 Exam 3, Out of Class, Due by December 8th, 2015 at 5:00 pm. Name: Problem 1. (15 points) A random variable is said to have the (standard) Cauchy distribution if its PDF is given by f (x) = 1 π 1 1+ x2 , −∞< x <∞ This problem uses computer simulations to demonstrate that a) samples from this distribution often have extreme outliers (a consequence of the heavy tails of the distribution), and b) the sample mean is prone to the same type of outliers. Below is a graph of the pdf a) (5 points) The R commands x=rcauchy(500); summary(x) generate a random sample of size 500 from the Cauchy distribution and display the sample’s five number summary; Report the five number summary and the interquartile range, and comment on whether or not the smallest and largest numbers generated from this sample of 500 are outliers. Repeat this 10 times. b) (5 points) The R commands m=matrix(rcauchy(50000), nrow=500); xb=apply(m,1,mean);summary(xb) generate the matrix m that has 500 rows, each of which is a sample of size n=100 from the Cauchy distribution, compute the 500 sample means and store them in xb. and display the five number summary xb. Repeat these commands 10 times, and report the 10 sets of five number summaries. Compare with the 10 sets of five number summaries from part (a), and comment on whether or not the distribution of the averages seems to be more prone to extreme outliers as that of the individual observations. c) (5 points) Why does this happen? (hint: try to calculate E(X) and V(X) for this distribution) and does the LLN and CLT apply for samples from a Cauchy distribution? Hint: E(X) is undefined for this distribution unless you use the Cauchy Principle Value as such for the mean lim a→∞ xf (x)dx −a a∫ In addition x2 1+ x2 dx = x2 +1−1 1+ x2 dx = 1− 1 1+ x2 " # $ % & ' ∫ ∫ ∫ dx 1 1+ x2 dx = tan−1 ∫ x +C Problem 2. (5 points) A marketing expert for a pasta-making company believes that 40% of pasta lovers prefer lasagna. If 9 out of 20 pasta lovers choose lasagna over other pastas, what can be concluded about the expert's claim? Use a 0.05 level of significance. Problem 3. (10 points) A coin is tossed 20 times, resulting in 5 heads. Is this sufficient evidence to reject the hypothesis that the coin is balanced in favor of the alternative that heads occur less than 50% of the time (essentially is this significant evidence to claim that the coin is unbalanced in favor of tails)? Use a 0.05 level of significance. Problem 4. (25 points) Since the chemical benzene may cause cancer, the federal government has set the maximum allowable benzene concentration in the workplace at 1 part per million (1 ppm) Suppose that a steel manufacturing plant is under investigation for possible violations regarding benzene level. The Occupational Safety and Health Administration (OSHA) will analyze 14 air samples over a one-month period. Assume normality of the population from which the samples were drawn. a) (3 points) What is an appropriate null hypothesis for this scenario? (Give this in symbols) b) (3 points) What is an appropriate alternative hypothesis for this scenario? (Give this in symbols) c) (3 points) What kind of hypothesis test is this: left-tailed, right-tailed or two-tailed? Explain how you picked your answer. d) (3 points) Is this a one-sample t-test or a one-sample test using a normal distribution? Explain how you picked your answer. e) (4 points) If the test using this sample of size 14 is to be done at the 1% significance level, calculate the critical value(s) and describe the rejection region(s) for the test statistic. Show your work. f) (5 points) OHSA finds the following for their sample of size 14: a mean benzene level of 1.51 ppm and a standard deviation of 1.415 ppm. What should be concluded at the 1% significance level? Support your answer with calculation(s) and reasoning. g) (4 points) Calculate the p-value for this test and verify that this answer would lead to the same conclusion you made in part f. Problem 5. (15 points) A normally distributed random variable Y possesses a mean of μ = 20 and a standard deviation of σ = 5. A random sample of n = 31 observations is to be selected. Let X be the sample average. (X in this problem is really x _ ) a)(5 points) Describe the sampling distribution of X (i.e. describe the distribution of X and give μx, σx ) b) (5 points) Find the z-score of x = 22 c) (5 points) Find P(X ≥ 22) = Problem 6. (10 points) A restaurants receipts show that the cost of customers' dinners has a distribution with a mean of $54 and a standard deviation of $18. What is the probability that the next 100 customers will spend a total of at least $5800 on dinner? Problem 7. (10 points) The operations manager of a large production plant would like to estimate the mean amount of time a worker takes to assemble a new electronic component. Assume that the standard deviation of this assembly time is 3.6 minutes and is normally distributed. a) (3 points) After observing 120 workers assembling similar devices, the manager noticed that their average time was 16.2 minutes. Construct a 92% confidence interval for the mean assembly time. b) (2 points) How many workers should be involved in this study in order to have the mean assembly time estimated up to ± 15 seconds with 92% confidence? c) (5 points) Construct a 92% confidence interval if instead of observing 120 workers assembling similar devices, rather the manager observes 25 workers and notice their average time was 16.2 minutes with a standard deviation of 4.0 minutes. Problem 8. (10 points): A manufacturer of candy must monitor the temperature at which the candies are baked. Too much variation will cause inconsistency in the taste of the candy. Past records show that the standard deviation of the temperature has been 1.2oF . A random sample of 30 batches of candy is selected, and the sample standard deviation of the temperature is 2.1oF . a. (5 points) At the 0.05 level of significance, is there evidence that the population standard deviation has increased above 1.2oF ? b. (3 points) What assumption do you need to make in order to perform this test? c. (2 points) Compute the p-value in (a) and interpret its meaning.

No expert has answered this question yet. You can browse … Read More...
art 1: Some of the more characteristic doctrines of the Enlightenment focused on the power and goodness of human rationality: 1) Reason is the most significant and positive capacity of the human; 2) reason enables one to break free from primitive, dogmatic, and superstitious beliefs holding one in the bonds of irrationality and ignorance; 3) in realizing the liberating potential of reason, one not only learns to think correctly, but to act correctly as well; 4) through philosophical and scientific progress, reason can lead humanity as a whole to a state of earthly perfection; 5) reason makes all humans equal and, therefore, deserving of equal liberty and treatment before the law; 6) beliefs of any sort should be accepted only on the basis of reason, and not on traditional or priestly authority; and 7) all human endeavors should seek to impart and develop knowledge, not feelings or character. (pbs.com) Benjamin Franklin, Thomas Paine, and Thomas Jefferson embodied the Age of Enlightenment. Use your choice of three of the seven doctrines to explain and prove these author’s philosophies. Make sure you draw on our readings to support your choices. Next, consider and discuss how these doctrines have been advanced, tested, and revised as the nation has grown and evolved. Part II: Briefly describe several, meaning more than two, of the conditions of the slave ship as experienced by Olaudah Equiano and related in his narrative. Compare his narrative to that of Phillis Wheatley’s experience. You must use selected quotes from each, but then interpret, in your own words, what the quotes mean and what their impact is on the reader.

art 1: Some of the more characteristic doctrines of the Enlightenment focused on the power and goodness of human rationality: 1) Reason is the most significant and positive capacity of the human; 2) reason enables one to break free from primitive, dogmatic, and superstitious beliefs holding one in the bonds of irrationality and ignorance; 3) in realizing the liberating potential of reason, one not only learns to think correctly, but to act correctly as well; 4) through philosophical and scientific progress, reason can lead humanity as a whole to a state of earthly perfection; 5) reason makes all humans equal and, therefore, deserving of equal liberty and treatment before the law; 6) beliefs of any sort should be accepted only on the basis of reason, and not on traditional or priestly authority; and 7) all human endeavors should seek to impart and develop knowledge, not feelings or character. (pbs.com) Benjamin Franklin, Thomas Paine, and Thomas Jefferson embodied the Age of Enlightenment. Use your choice of three of the seven doctrines to explain and prove these author’s philosophies. Make sure you draw on our readings to support your choices. Next, consider and discuss how these doctrines have been advanced, tested, and revised as the nation has grown and evolved. Part II: Briefly describe several, meaning more than two, of the conditions of the slave ship as experienced by Olaudah Equiano and related in his narrative. Compare his narrative to that of Phillis Wheatley’s experience. You must use selected quotes from each, but then interpret, in your own words, what the quotes mean and what their impact is on the reader.

info@checkyourstudy.com
Using the Earnings_and_Height dataset, perform the following exercises. 1. Test whether the difference in mean height for men and women is statistically significant? Is it? 2. Does the distribution of height for men and women in the US follow the normal distribution? Answer by looking at detailed summary statistics and high order moments of the data. 3. If you were to select one al observation from the data at random, what is the probability that individual is than sixty seven inches tall? 4a. Run the following regressions and interpret the coefficient on the height variable. I. Regress earnings on height II. Regress log of earning on height III. Regress log earnings on log of height 4b. which model is preferred? 5a. Regress log of earnings on height and height² 5b. is there a non-linear relationship between height and log earnings? 5c. Give a-formula for the effect of a change in height on the change in log earnings. 6. Create the following variables: I. A dummy variable for being-Hispania. ii. A dummy variable for being black. iii. A dummy variable for being female. iv. A set of region dummy variables. 7a. Run the following regression separately by gender: Regress log earnings on height education age black Hispanic 7b. Is there a difference in the estimated effect of height on earnings by gender? 8. Run the following regression: Regress log earnings on height education age black Hispanic female and a set of region indicators, and perform the following tests (and interpret the results): I. Test for the equality of coefficients on the Hispanic and black variables. ii. Test the hypothesis that the coefficients on female, black and Hispanic are all zero. 9a. Run the following regression for men: Regress log earnings on height height² education age black Hispanic and a set of region indicators. Is there evidence of a non-linear relationship between height andlog earnings for men? 9b. Estimate the effect of a one inch increase in height on log earnings for a man starting an average height) 10. Discuss the following threats to internal validity regarding the model in (8): I. measurement error focusing on earnings and height) ii. Omitted variables bias

Using the Earnings_and_Height dataset, perform the following exercises. 1. Test whether the difference in mean height for men and women is statistically significant? Is it? 2. Does the distribution of height for men and women in the US follow the normal distribution? Answer by looking at detailed summary statistics and high order moments of the data. 3. If you were to select one al observation from the data at random, what is the probability that individual is than sixty seven inches tall? 4a. Run the following regressions and interpret the coefficient on the height variable. I. Regress earnings on height II. Regress log of earning on height III. Regress log earnings on log of height 4b. which model is preferred? 5a. Regress log of earnings on height and height² 5b. is there a non-linear relationship between height and log earnings? 5c. Give a-formula for the effect of a change in height on the change in log earnings. 6. Create the following variables: I. A dummy variable for being-Hispania. ii. A dummy variable for being black. iii. A dummy variable for being female. iv. A set of region dummy variables. 7a. Run the following regression separately by gender: Regress log earnings on height education age black Hispanic 7b. Is there a difference in the estimated effect of height on earnings by gender? 8. Run the following regression: Regress log earnings on height education age black Hispanic female and a set of region indicators, and perform the following tests (and interpret the results): I. Test for the equality of coefficients on the Hispanic and black variables. ii. Test the hypothesis that the coefficients on female, black and Hispanic are all zero. 9a. Run the following regression for men: Regress log earnings on height height² education age black Hispanic and a set of region indicators. Is there evidence of a non-linear relationship between height andlog earnings for men? 9b. Estimate the effect of a one inch increase in height on log earnings for a man starting an average height) 10. Discuss the following threats to internal validity regarding the model in (8): I. measurement error focusing on earnings and height) ii. Omitted variables bias

No expert has answered this question yet. You can browse … Read More...
Define: 41 Things Philosophy is: 1. Ignorant 2. Selfish 3. Ironic 4. Plain 5. Misunderstood 6. A failure 7. Poor 8. Unscientific 9. Unteachable 10. Foolish 11. Abnormal 12. Divine trickery 13. Egalitarian 14. A divine calling 15. Laborious 16. Countercultural 17. Uncomfortable 18. Virtuous 19. Dangerous 20. Simplistic<br />21. Polemical 22. Therapeutic 23. “conformist” 24. Embarrassi ng 25. Invulnerable 26. Annoying 27. Pneumatic 28. Apolitic al 29. Docile/teachable 30. Messianic 31. Pious 32. Impract ical 33. Happy 34. Necessary 35. Death-defying 36. Fallible 37. Immortal 38. Confident 39. Painful 40. agnostic</br

Define: 41 Things Philosophy is: 1. Ignorant 2. Selfish 3. Ironic 4. Plain 5. Misunderstood 6. A failure 7. Poor 8. Unscientific 9. Unteachable 10. Foolish 11. Abnormal 12. Divine trickery 13. Egalitarian 14. A divine calling 15. Laborious 16. Countercultural 17. Uncomfortable 18. Virtuous 19. Dangerous 20. Simplistic
21. Polemical 22. Therapeutic 23. “conformist” 24. Embarrassi ng 25. Invulnerable 26. Annoying 27. Pneumatic 28. Apolitic al 29. Docile/teachable 30. Messianic 31. Pious 32. Impract ical 33. Happy 34. Necessary 35. Death-defying 36. Fallible 37. Immortal 38. Confident 39. Painful 40. agnostic

Ignorant- A person is said to be ignorant if he … Read More...
Name___________________________________ Period_____ Investigation: Making Waves PART I: Objectives: • Learn vocabulary describing waves • Calculate the speed of a wave • Understand how amplitude affects the speed of a wave • Understand how frequency and wavelength affect the speed of a wave Open this web site: http://phet.colorado.edu/new/simulations/sims.php?sim=Wave_on_a_String You can click on Run Now! to run the simulation online, or Run Offline to save it to your desktop. It might run faster this way. Start by Wiggling the Wrench. Spend about 5 minutes experimenting with the Tension, Manual/Pulse/Oscillate, Fixed/Loose/No end, and changing the Amplitude, Frequency and Damping. Click on Show Rulers and Timer. Practice moving the rulers around and starting/resetting the timer. Click on the Pause/Play and Step buttons to see how they work. Use these settings: Pulse, Amplitude=50, Pulse Width=35, Damping=0, Tension at High and No End. NOTE that the amplitude is just a relative scale (not centimeters). Send a single pulse down the string. This is called a TRANSVERSE PULSE. Watch the motion of the green dots.  1. As the pulse goes by from left to right, in what direction does the string move? ________________________________________________________________________________________________________________________________________________  2. A definition of TRANSVERSE is “lying across”. Why is TRANSVERSE a good name for the wave you just observed? ________________________________________________________________________________________________________________________________________________ Make another pulse, and then PAUSE the wave. Use the vertical ruler to measure the amplitude of the wave in centimeters. This is the distance from the dotted orange line to the crest of the wave. Record the amplitude in Table 1 in the first row. Now, measure the time for a pulse to travel 100 cm. To do this: • Reset the clock to 0:00 and reset the generator • Click Pause/Play—it should say PAUSED on the screen • Click Pulse • Click Pause/Play again to start a timed pulse. Pause again just as the crest (peak) of the pulse touches the window 100 cm away. Record the time for a pulse to travel 100 cm in Table 1. Run 3 time trials, and record in the table. Calculate the average time. Now, measure the amplitude and timing of pulses for two other amplitudes (one smaller than 50, one larger than 50). Do three trials at each amplitude and calculate the average times. Calculate the average wave speed for each of the three amplitudes. See below for a sample calculation. Table 1 Your measured amplitude, cm Time for pulse to travel 100 cm, seconds Average time, seconds Speed=length of string / average time Example of speed calculation: Speed = string length/ average time Speed = 100 cm/2 seconds = 50 cm/second  3. How does the amplitude of a wave affect the speed of a wave? ________________________________________________________________________ Use these settings: Oscillate, Fixed end. Try amplitude=20, frequency=51, damping=0. The result is called a periodic wave. 4. Describe the appearance of the wave you created. ________________________________________________________________________________________________________________________________________________________________________________________________________________________ You should see waves that do not move along the string. You will also see points where the string does not move at all. These waves are called STANDING WAVES. The points where the wave doesn’t move are called NODES. Pause the simulation.  5. Draw the standing wave in the box below, labeling the AMPLITUDE, WAVELENGTH and NODES of a standing wave. Use these settings: Amplitude=20, Frequency=50, Damping=0, Oscillate, No End. Reset the clock. You can also measure the wave frequency. To do this, you should pair up with another student if possible. Watch the piston go up and down to make the wave. One up and down motion represents one wave. Use the clock to measure the time required for 10 complete cycles or waves. You will also need to PAUSE the wave to measure the wavelength of the wave in centimeters (cm). The frequency of the wave is calculated in the following way: Frequency = 10 waves/# seconds for 10 cycles For example, 10 waves/5 seconds = 2 cycles per second, or 2 Hertz. Make several waves by changing the wave frequency—use numbers over 30 on the scale. For each wave, measure the wavelength using the ruler. Now, calculate the frequency. See the example in the first row of Table 2. Record the wavelength and frequency of three waves with different wavelengths. Wavelength (cm) Frequency (cycles/second or Hertz) Speed (cm/s) = Wavelength x frequency 33 cm 10 waves/5.45 sec = 1.8 Hertz 33 cm x 1.8 Hertz = 59.4 cm/second Based on the equation used to calculate the speed of a wave, answer questions 6 and 7.  6. If you increase the wavelength of a wave, how does the speed change? ________________________________________________________________________________________________________________________________________________  7. If you increase the frequency of a wave, how does the speed change? ________________________________________________________________________________________________________________________________________________ Part II: Objectives: • Interpret a 2D top view picture of a wave • Identify areas of constructive and destructive interference in 2D • Predict the behavior of water, sound, or light when you have two sources o What will happen in constructive areas o What will happen in destructive areas 1) Open the “Wave Interference” simulation from the PhET website (in Sound & Waves) 2) On the water simulation, what does the crest (peak) of the wave look like in the top view? What does the trough look like? 3) When you add two drips, what changes about the waves’ patterns? 4) What does the wave look like in the area that the two waves constructively interfere? Describe both the top view and what the side view would look like. a. TOP: b. SIDE: 5) What does the wave look like in the area that the two waves destructively interfere? Describe both the top view and what the side view would look like. a. TOP: b. SIDE: 6) Switch to the sound simulation. a. What do you think will happen when you put two speakers next to each other? b. Why do you think this will happen? c. Try it (putting two speakers together) and tell me what happened. 7) Now switch to the light simulation. a. What do you think will happen when you put two light sources next to each other? b. Why do you think this will happen? c. Try it (putting two light sources together) and tell me what happened. d. What happens when you use one light source and two slits? 8) What is similar about all three of these simulations (i.e. water, sound & light)? 9) How do I know that these things are waves and not particles? (Think about what would happen in the two slit experiment if they were particles).

Name___________________________________ Period_____ Investigation: Making Waves PART I: Objectives: • Learn vocabulary describing waves • Calculate the speed of a wave • Understand how amplitude affects the speed of a wave • Understand how frequency and wavelength affect the speed of a wave Open this web site: http://phet.colorado.edu/new/simulations/sims.php?sim=Wave_on_a_String You can click on Run Now! to run the simulation online, or Run Offline to save it to your desktop. It might run faster this way. Start by Wiggling the Wrench. Spend about 5 minutes experimenting with the Tension, Manual/Pulse/Oscillate, Fixed/Loose/No end, and changing the Amplitude, Frequency and Damping. Click on Show Rulers and Timer. Practice moving the rulers around and starting/resetting the timer. Click on the Pause/Play and Step buttons to see how they work. Use these settings: Pulse, Amplitude=50, Pulse Width=35, Damping=0, Tension at High and No End. NOTE that the amplitude is just a relative scale (not centimeters). Send a single pulse down the string. This is called a TRANSVERSE PULSE. Watch the motion of the green dots.  1. As the pulse goes by from left to right, in what direction does the string move? ________________________________________________________________________________________________________________________________________________  2. A definition of TRANSVERSE is “lying across”. Why is TRANSVERSE a good name for the wave you just observed? ________________________________________________________________________________________________________________________________________________ Make another pulse, and then PAUSE the wave. Use the vertical ruler to measure the amplitude of the wave in centimeters. This is the distance from the dotted orange line to the crest of the wave. Record the amplitude in Table 1 in the first row. Now, measure the time for a pulse to travel 100 cm. To do this: • Reset the clock to 0:00 and reset the generator • Click Pause/Play—it should say PAUSED on the screen • Click Pulse • Click Pause/Play again to start a timed pulse. Pause again just as the crest (peak) of the pulse touches the window 100 cm away. Record the time for a pulse to travel 100 cm in Table 1. Run 3 time trials, and record in the table. Calculate the average time. Now, measure the amplitude and timing of pulses for two other amplitudes (one smaller than 50, one larger than 50). Do three trials at each amplitude and calculate the average times. Calculate the average wave speed for each of the three amplitudes. See below for a sample calculation. Table 1 Your measured amplitude, cm Time for pulse to travel 100 cm, seconds Average time, seconds Speed=length of string / average time Example of speed calculation: Speed = string length/ average time Speed = 100 cm/2 seconds = 50 cm/second  3. How does the amplitude of a wave affect the speed of a wave? ________________________________________________________________________ Use these settings: Oscillate, Fixed end. Try amplitude=20, frequency=51, damping=0. The result is called a periodic wave. 4. Describe the appearance of the wave you created. ________________________________________________________________________________________________________________________________________________________________________________________________________________________ You should see waves that do not move along the string. You will also see points where the string does not move at all. These waves are called STANDING WAVES. The points where the wave doesn’t move are called NODES. Pause the simulation.  5. Draw the standing wave in the box below, labeling the AMPLITUDE, WAVELENGTH and NODES of a standing wave. Use these settings: Amplitude=20, Frequency=50, Damping=0, Oscillate, No End. Reset the clock. You can also measure the wave frequency. To do this, you should pair up with another student if possible. Watch the piston go up and down to make the wave. One up and down motion represents one wave. Use the clock to measure the time required for 10 complete cycles or waves. You will also need to PAUSE the wave to measure the wavelength of the wave in centimeters (cm). The frequency of the wave is calculated in the following way: Frequency = 10 waves/# seconds for 10 cycles For example, 10 waves/5 seconds = 2 cycles per second, or 2 Hertz. Make several waves by changing the wave frequency—use numbers over 30 on the scale. For each wave, measure the wavelength using the ruler. Now, calculate the frequency. See the example in the first row of Table 2. Record the wavelength and frequency of three waves with different wavelengths. Wavelength (cm) Frequency (cycles/second or Hertz) Speed (cm/s) = Wavelength x frequency 33 cm 10 waves/5.45 sec = 1.8 Hertz 33 cm x 1.8 Hertz = 59.4 cm/second Based on the equation used to calculate the speed of a wave, answer questions 6 and 7.  6. If you increase the wavelength of a wave, how does the speed change? ________________________________________________________________________________________________________________________________________________  7. If you increase the frequency of a wave, how does the speed change? ________________________________________________________________________________________________________________________________________________ Part II: Objectives: • Interpret a 2D top view picture of a wave • Identify areas of constructive and destructive interference in 2D • Predict the behavior of water, sound, or light when you have two sources o What will happen in constructive areas o What will happen in destructive areas 1) Open the “Wave Interference” simulation from the PhET website (in Sound & Waves) 2) On the water simulation, what does the crest (peak) of the wave look like in the top view? What does the trough look like? 3) When you add two drips, what changes about the waves’ patterns? 4) What does the wave look like in the area that the two waves constructively interfere? Describe both the top view and what the side view would look like. a. TOP: b. SIDE: 5) What does the wave look like in the area that the two waves destructively interfere? Describe both the top view and what the side view would look like. a. TOP: b. SIDE: 6) Switch to the sound simulation. a. What do you think will happen when you put two speakers next to each other? b. Why do you think this will happen? c. Try it (putting two speakers together) and tell me what happened. 7) Now switch to the light simulation. a. What do you think will happen when you put two light sources next to each other? b. Why do you think this will happen? c. Try it (putting two light sources together) and tell me what happened. d. What happens when you use one light source and two slits? 8) What is similar about all three of these simulations (i.e. water, sound & light)? 9) How do I know that these things are waves and not particles? (Think about what would happen in the two slit experiment if they were particles).

4. Using your knowledge of the Stevenson’s career management model identify and briefly describe one activity that should be included in an organization’s career management program. Identify which element of the model the activity you identified fits within.

4. Using your knowledge of the Stevenson’s career management model identify and briefly describe one activity that should be included in an organization’s career management program. Identify which element of the model the activity you identified fits within.

Discipline Expertise- There is an apparent type of interdisciplinary in … Read More...
Lab Report Name Simple Harmonic motion Date: Objective or purpose: The main objective of this lab is to find the value of the spring constant (k) according to Hooke’s law. This lab also teaches us curve fitting and its application here in this lab.

Lab Report Name Simple Harmonic motion Date: Objective or purpose: The main objective of this lab is to find the value of the spring constant (k) according to Hooke’s law. This lab also teaches us curve fitting and its application here in this lab.

Name Simple Harmonic motion Date:           … Read More...