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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CEE 260 / MIE 273 Probability & Statistics Name: Final Exam, version D — 100 points (120 minutes) PLEASE READ QUESTIONS CAREFULLY and SHOW YOUR WORK! CALCULATORS PERMITTED – ABSOLUTELY NO REFERENCES! 1. Suppose the waiting time (in minutes) for your 911 SC Targa to reach operating temperature in the morning is uniformly distributed on [0,10], while the waiting time in the evening is uniformly distributed on [0,5] independent of morning waiting time. a. (5%) If you drive your Targa each morning and evening for a week (5 morning and 5 evening rides), what is the variance of your total waiting time? b. (5%) What is the expected value of the difference between morning and evening waiting time on a given day? 2. (10%) Find the maximum likelihood estimator (MLE) of ϴ when Xi ~ Exponential(ϴ) and you have observed X1, X2, X3, …, Xn. 2 3. The waiting time for delivery of a new Porsche 911 Carrera at the local dealership is distributed exponentially with a population mean of 3.55 months and population standard deviation of 1.1 months. Recently, in an effort to reduce the waiting time, the dealership has experimented with an online ordering system. A sample of 100 customers during a recent sales promotion generated a mean waiting time of 3.18 months using the new system. Assume that the population standard deviation of the waiting time has not changed from 1.1 months. (hint: the source distribution is irrelevant, but its parameters are relevant) a. (15%) What is the probability that the average wait time is between 3.2 and 6.4 months? (hint: draw a sketch for full credit) b. (10%) At the 0.05 level of significance, using the critical values approach to hypothesis testing, is there evidence that the population mean waiting time to accept delivery is less than 3.55 months? c. (10%) At the 0.01 level of significance, using the p-value approach to hypothesis testing, is there evidence that the population mean waiting time to accept delivery is less than 3.55 months? 3 4. Porsche AG is a leading manufacturer of performance automobiles. The 911 Carrera model, Porsche’s premier sports car, reaches a top track speed of 180 miles per hour. Engineers claim the new advanced technology 911 GT2 automatically adjusts its top speed depending on the weather conditions. Suppose that in an effort to test this claim, Porsche selects a few 911 GT2 models to test drive on the company track in Stuttgart, Germany. The average top speed for the sample of 25 test drives is 182.36 mph, with a standard deviation of 7.24 mph. a. (5%) Without using complete sentences, what might be some problems with the sampling conducted above? Identify and explain at least 2. b. (15%) Using the critical values approach to hypothesis testing and a 0.10 level of significance, is there evidence that the mean top track speed is different for the 911 GT2? (hint: state the null and alternative hypotheses, draw a sketch, and show your work for full credit) c. (10%) Set up a 95% confidence interval estimate of the population mean top speed of the 911 GT2. d. (5%) Compare the results of (b) and (c). What conclusions do you reach about the top speed of the new 911 GT2? 4 5. (10%) Porsche USA believes that sales of the venerable 911 Carrera are a function of annual income (in thousands of dollars) and a risk tolerance index of the potential buyer. Determine the regression equation and provide a succinct analysis of Porsche’s conjecture using the following Excel results. SUMMARY OUTPUT Regression Stat istics Multiple R 0.805073 R Square 0.648142 Adjusted R Square 0.606747 Standard Error 7.76312 Observations 20 ANOVA df SS MS F Significance F Regression 2 1887.227445 943.6137225 15.65747206 0.000139355 Residual 17 1024.522555 60.26603265 Total 19 2911.75 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 23.50557 6.845545641 3.433702952 0.003167982 9.062731576 37.94840898 Income 0.613408 0.125421229 4.890786567 0.000137795 0.348792801 0.878024121 Risk Index -0.00126 0.004519817 -0.278357691 0.784095184 -0.010794106 0.008277854 BONUS (5 points) What is the probability that 2 or more students in our class of 22 have the same birthday?

CEE 260 / MIE 273 Probability & Statistics Name: Final Exam, version D — 100 points (120 minutes) PLEASE READ QUESTIONS CAREFULLY and SHOW YOUR WORK! CALCULATORS PERMITTED – ABSOLUTELY NO REFERENCES! 1. Suppose the waiting time (in minutes) for your 911 SC Targa to reach operating temperature in the morning is uniformly distributed on [0,10], while the waiting time in the evening is uniformly distributed on [0,5] independent of morning waiting time. a. (5%) If you drive your Targa each morning and evening for a week (5 morning and 5 evening rides), what is the variance of your total waiting time? b. (5%) What is the expected value of the difference between morning and evening waiting time on a given day? 2. (10%) Find the maximum likelihood estimator (MLE) of ϴ when Xi ~ Exponential(ϴ) and you have observed X1, X2, X3, …, Xn. 2 3. The waiting time for delivery of a new Porsche 911 Carrera at the local dealership is distributed exponentially with a population mean of 3.55 months and population standard deviation of 1.1 months. Recently, in an effort to reduce the waiting time, the dealership has experimented with an online ordering system. A sample of 100 customers during a recent sales promotion generated a mean waiting time of 3.18 months using the new system. Assume that the population standard deviation of the waiting time has not changed from 1.1 months. (hint: the source distribution is irrelevant, but its parameters are relevant) a. (15%) What is the probability that the average wait time is between 3.2 and 6.4 months? (hint: draw a sketch for full credit) b. (10%) At the 0.05 level of significance, using the critical values approach to hypothesis testing, is there evidence that the population mean waiting time to accept delivery is less than 3.55 months? c. (10%) At the 0.01 level of significance, using the p-value approach to hypothesis testing, is there evidence that the population mean waiting time to accept delivery is less than 3.55 months? 3 4. Porsche AG is a leading manufacturer of performance automobiles. The 911 Carrera model, Porsche’s premier sports car, reaches a top track speed of 180 miles per hour. Engineers claim the new advanced technology 911 GT2 automatically adjusts its top speed depending on the weather conditions. Suppose that in an effort to test this claim, Porsche selects a few 911 GT2 models to test drive on the company track in Stuttgart, Germany. The average top speed for the sample of 25 test drives is 182.36 mph, with a standard deviation of 7.24 mph. a. (5%) Without using complete sentences, what might be some problems with the sampling conducted above? Identify and explain at least 2. b. (15%) Using the critical values approach to hypothesis testing and a 0.10 level of significance, is there evidence that the mean top track speed is different for the 911 GT2? (hint: state the null and alternative hypotheses, draw a sketch, and show your work for full credit) c. (10%) Set up a 95% confidence interval estimate of the population mean top speed of the 911 GT2. d. (5%) Compare the results of (b) and (c). What conclusions do you reach about the top speed of the new 911 GT2? 4 5. (10%) Porsche USA believes that sales of the venerable 911 Carrera are a function of annual income (in thousands of dollars) and a risk tolerance index of the potential buyer. Determine the regression equation and provide a succinct analysis of Porsche’s conjecture using the following Excel results. SUMMARY OUTPUT Regression Stat istics Multiple R 0.805073 R Square 0.648142 Adjusted R Square 0.606747 Standard Error 7.76312 Observations 20 ANOVA df SS MS F Significance F Regression 2 1887.227445 943.6137225 15.65747206 0.000139355 Residual 17 1024.522555 60.26603265 Total 19 2911.75 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 23.50557 6.845545641 3.433702952 0.003167982 9.062731576 37.94840898 Income 0.613408 0.125421229 4.890786567 0.000137795 0.348792801 0.878024121 Risk Index -0.00126 0.004519817 -0.278357691 0.784095184 -0.010794106 0.008277854 BONUS (5 points) What is the probability that 2 or more students in our class of 22 have the same birthday?

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Homework #8  Consider the veracity or falsehood of each of the following statements. For bonus, argue for those that you believe are true while providing a counterexample for those that you believe are false.  If the first and third rows of A are equal, then det A 0.  If P is a projection, then uCP if and only if Pu  u.  If P is a projection, and detP  0, then P  I .  If A has determinant 10, then 1 A has determinant 1 10 .  If B is invertible, 1 1 det(A B ) det A (detB) .  If P is a projection, and R  2P I , then 2 R  I .  If P is a projection, and P  I , then detP  0 .  Short Computations. All of the following do not involve long computations:  Suppose 1 2 1 5 1 8 A                  and 1 9 2 4 3 1 A                   . Compute 7 13 19 A         .  Compute               0 8 7 1 0 2 3 4 5 3 0 9 2 0 0 0 3 0 0 0 1 9 3 2 0 det .  Use Cramer’s Rule to find 5 x (hint: you do not need your calculator). 1 2 3 4 5 5x 2x 8x x 3x 13 1 3 3x 5x 0 1 3 5 3x 3x 3x 9 1 2 3 5 3x 2x x 2x 7 1 3 x 4x 0 Let A 1 2 3 4 1 3 4 6 2 5 13 15 4 10 15 31 . Given is that det A  61. Do the following:  1 1 2 4 2 3 5 10 3 4 13 15 4 6 15 31 det  det2A  1 3 4 6 2 4 6 8 2 5 13 15 4 10 15 31 det  1 3 4 6 2 5 13 15 4 10 15 31 1 2 3 4 det  Consider the matrix A  0 1 0 0 0 0 1 0 0 0 0 1 1 2 2 1           . Use row (or column) expansion to compute det(xI A) .  The matrix 4 1 1 2 1 1 1 4 1 1 2 1 1 1 4 1 1 2 2 1 1 4 1 1 1 2 1 1 4 1 1 1 2 1 1 4 1 6 P is the projection matrix for the column space of matrix A. This matrix A is also known to be of full rank. Answer the following, giving reasons for your answers.  Find a transparent basis and the dimension for the column space of P.  Find a basis and the dimension for the column space of A .  What size is the matrix A ?  Find a transparent basis and the dimension for the null space of P.  Find a transparent basis and the dimension for the row space of P.  Find a basis and the dimension for the null space of A.  For which of the following b can you find a solution to the system Ax b ? This does not mean you should find a solution, only whether one could or not. 10 17 19 14 10 17 19 14 13 10 17 19 14 13 23 1 1 1 1 1 1 .  It is known that certain vector u is a solution to the system Ax c . Give all solutions to Ax c .  It is also known that 1 2 3 4 5 6 Ax does not have a solution. How would you change the constant vector so that there would be a solution? Extra Problems.  Fill in the blank with the best possible expression to complete the sentence truthfully. Only that one will be counted correct. 1. matrix with two equal columns will have zero determinant. 1 2 3 Some Every No 2. If A is invertible, then A commute with its inverse. 1 2 3 must always can will not 3. If A is 6  9 , then the columns of A be linearly independent. While in AT , the columns be linearly independent. 1 2 3 can have to cannot 4. Let A be square, and suppose Ax  0 has a nontrivial solution. Then detA equal 0. 1 2 3 may cannot must 5. Let A and B be 3 3. Then det (AB) equal det(A)det(B) . 1 2 3 could must couldn’t 6. Let A be square and suppose detA  0. Then have an inverse 1 2 3 will not may must always 7. Let A and B be 2  2 . Then det (A B) equal det(A)  det(B) . 1 2 3 could must could not 8. exist a 6  6 matrix all of whose entries are whole numbers and its determinant is 2 5 . 1 2 3 There does There does not There might Bonus: Consider the matrix 0 0 1 0 2 0 n 0 . Give its determinant as a function of n.

Homework #8  Consider the veracity or falsehood of each of the following statements. For bonus, argue for those that you believe are true while providing a counterexample for those that you believe are false.  If the first and third rows of A are equal, then det A 0.  If P is a projection, then uCP if and only if Pu  u.  If P is a projection, and detP  0, then P  I .  If A has determinant 10, then 1 A has determinant 1 10 .  If B is invertible, 1 1 det(A B ) det A (detB) .  If P is a projection, and R  2P I , then 2 R  I .  If P is a projection, and P  I , then detP  0 .  Short Computations. All of the following do not involve long computations:  Suppose 1 2 1 5 1 8 A                  and 1 9 2 4 3 1 A                   . Compute 7 13 19 A         .  Compute               0 8 7 1 0 2 3 4 5 3 0 9 2 0 0 0 3 0 0 0 1 9 3 2 0 det .  Use Cramer’s Rule to find 5 x (hint: you do not need your calculator). 1 2 3 4 5 5x 2x 8x x 3x 13 1 3 3x 5x 0 1 3 5 3x 3x 3x 9 1 2 3 5 3x 2x x 2x 7 1 3 x 4x 0 Let A 1 2 3 4 1 3 4 6 2 5 13 15 4 10 15 31 . Given is that det A  61. Do the following:  1 1 2 4 2 3 5 10 3 4 13 15 4 6 15 31 det  det2A  1 3 4 6 2 4 6 8 2 5 13 15 4 10 15 31 det  1 3 4 6 2 5 13 15 4 10 15 31 1 2 3 4 det  Consider the matrix A  0 1 0 0 0 0 1 0 0 0 0 1 1 2 2 1           . Use row (or column) expansion to compute det(xI A) .  The matrix 4 1 1 2 1 1 1 4 1 1 2 1 1 1 4 1 1 2 2 1 1 4 1 1 1 2 1 1 4 1 1 1 2 1 1 4 1 6 P is the projection matrix for the column space of matrix A. This matrix A is also known to be of full rank. Answer the following, giving reasons for your answers.  Find a transparent basis and the dimension for the column space of P.  Find a basis and the dimension for the column space of A .  What size is the matrix A ?  Find a transparent basis and the dimension for the null space of P.  Find a transparent basis and the dimension for the row space of P.  Find a basis and the dimension for the null space of A.  For which of the following b can you find a solution to the system Ax b ? This does not mean you should find a solution, only whether one could or not. 10 17 19 14 10 17 19 14 13 10 17 19 14 13 23 1 1 1 1 1 1 .  It is known that certain vector u is a solution to the system Ax c . Give all solutions to Ax c .  It is also known that 1 2 3 4 5 6 Ax does not have a solution. How would you change the constant vector so that there would be a solution? Extra Problems.  Fill in the blank with the best possible expression to complete the sentence truthfully. Only that one will be counted correct. 1. matrix with two equal columns will have zero determinant. 1 2 3 Some Every No 2. If A is invertible, then A commute with its inverse. 1 2 3 must always can will not 3. If A is 6  9 , then the columns of A be linearly independent. While in AT , the columns be linearly independent. 1 2 3 can have to cannot 4. Let A be square, and suppose Ax  0 has a nontrivial solution. Then detA equal 0. 1 2 3 may cannot must 5. Let A and B be 3 3. Then det (AB) equal det(A)det(B) . 1 2 3 could must couldn’t 6. Let A be square and suppose detA  0. Then have an inverse 1 2 3 will not may must always 7. Let A and B be 2  2 . Then det (A B) equal det(A)  det(B) . 1 2 3 could must could not 8. exist a 6  6 matrix all of whose entries are whole numbers and its determinant is 2 5 . 1 2 3 There does There does not There might Bonus: Consider the matrix 0 0 1 0 2 0 n 0 . Give its determinant as a function of n.

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Fact Debate Brief Introduction Crime doesn’t pay; it should be punished. Even since childhood, a slap on the hand has prevented possible criminals from ever committing the same offense; whether it was successful or not depended on how much that child wanted that cookie. While a slap on the wrist might or might not be an effective deterrent, the same can be said about the death penalty. Every day, somewhere in the world, a criminal is stopped permanently from committing any future costs, but this is by the means of the death. While effective in stopping one person permanently, it does nothing about the crime world as a whole. While it is necessary to end the career of a criminal, no matter what his or her crime is, we must not end it by taking a life. Through this paper, the death penalty will be proven ineffective at deterring crime by use of other environmental factors. Definition: The death penalty is defined as the universal punishment of death as legally applied by a fair court system. It is important for it to be a fair legal system, as not to confuse it with genocide, mob mentality, or any other ruling without trial. Claim 1: Use of the death penalty is in decline Ground 1: According to the book The Death Penalty: A Worldwide Perspective by Roger Hood and Carolyn Hoyle, published Dec. 8th, 2014, the Oxford professors in criminology say “As in most of the rest of the world, the death penalty in the US is in decline and distributed unevenly in frequency of use” even addressing that, as of April 2014, 18 states no longer have a death penalty, and even Oregon and Washington are considering removing their death penalty laws. Furthermore, in 2013, only 9 of these states still retaining the death penalty actually executed someone. Warrant 1: The death penalty can be reinstated at any time, but so far, it hasn’t been. At the same time, more states consider getting rid of it altogether. Therefore, it becomes clear that even states don’t want to be involved with this process showing that this is a disliked process. Claim 2: Even states with death penalty in effect still have high crime rates. Ground 2: With the reports gathered from fbi.gov, lawstreetmedia.com, a website based around political expertise and research determined the ranking of each state based on violent crime, published September 12th, 2014. Of the top ten most violent states, only three of which had the death penalty instituted (Maryland #9, New Mexico #4, Alaska #3). The other seven still had the system in place, and, despite it, still have a high amount of violent crime. On the opposite end of the spectrum, at the bottom ten most violent states, four of which, including the bottom-most states, do not have the death penalty in place. Warrant 2: With this ranking, it literally proves that the death penalty does not deter crime, or that there is a correlation between having the death penalty and having a decrease in the crime rate. Therefore, the idea of death penalty deterring crime is a null term in the sense that there is no, or a flawed connection. Claim 3: Violent crime is decreasing (but not because if the death penalty) Ground 3 A: According to an article published by The Economist, dated July 23rd, 2013, the rate of violent crime is in fact decreasing, but not because of the death penalty, but rather, because we have more police. From 1995 to 2010, policing has increased one-fifth, and with it, a decline in crime rate. In fact, in cities such as Detroit where policing has been cut, an opposite effect, an increase in crime, has been reported. Ground 3 B: An article from the Wall Street Journal, dated May 28th, 2011, also cites a decline in violent, only this time, citing the reason as a correlation with poverty levels. In 2009, at the start of the housing crisis, crime rates also dropped noticeably. Oddly enough, this article points out the belief that unemployment is often associated with crime; instead, the evidence presented is environmental in nature. Warrant 3: Crime rate isn’t deterred by death penalty, but rather, our surroundings. Seeing as how conditions have improved, so has the state of peace. Therefore, it becomes clear that the death penalty is ineffective at deterring crime because other key factors present more possibility for improvement of society. Claim 4: The death penalty is a historically flawed system. Ground 4A: According to the book The Death Penalty: Constitutional Issues, Commentaries, and Case Briefs by Scott Vollum, published in 2005, addresses how the case of the death penalty emerged to where it is today. While the book is now a decade old, it is used for historical context, particularly, in describing the first execution that took place in 1608. While it is true that most of these executions weren’t as well-grounded as the modern ones that take place now, they still had no effect in deterring crime. Why? Because even after America was established and more sane, the death penalty still had to be used because criminals still had violent behaviors. Ground 4B: According to data from Mother Jones, published May 17th, 2013, the reason why the crime rate was so high in the past could possibly be due to yet another environmental factor (affected by change over time), exposure to lead. Since the removal of lead from paint started over a hundred years ago, there has been a decline in homicide. Why is this important? Lead poisoning in child’s brain, if not lethal, can affect development and lead to mental disability, lower IQ, and lack of reasoning. Warrant 4: By examining history as a whole, there is a greater correlation between other factors that have resulted in a decline in violent crime. The decline in the crime rate has been an ongoing process, but has shown a faster decline due to other environmental factors, rather than the instatement of the death penalty. Claim 5: The world’s violent crime rate is changing, but not due to the death penalty. Ground 5A: According to article published by Amnesty USA in March of 2014, the number of executions under the death penalty reported in 2013 had increased by 15%. However, the rate of violent crime in the world has decreased significantly in the last decade. But, Latvia, for example, has permanently banned the death penalty since 2012. In 2014, the country was viewed overall as safe and low in violent crime rate. Ground 5B: However, while it is true that there is a decline in violent crime rate worldwide, The World Bank, April 17, 2013, reports that the rate of global poverty is decreasing. In a similar vein to the US, because wealth is being distributed better and conditions are improving overall, there is a steady decline in crime rate. Warrant 5: By examining the world as a whole, it becomes clear that it doesn’t matter if the death penalty is in place, violent crime will still exist. However, mirroring the US, as simple conditions improve, so does lifestyle. The death penalty does not deter crime in the world, rather a better quality of life is responsible for that. Works Cited “Death Sentences and Executions 2013.” Amnesty International USA. Amnesty USA, 26 Mar. 2014. Web. 15 Mar. 2015. <http://www.amnestyusa.org/research/reports/death-sentences-and-executions-2013>. D. K. “Why Is Crime Falling?” The Economist. The Economist Newspaper, 23 July 2013. Web. 12 Mar. 2015. <http://www.economist.com/blogs/economist-explains/2013/07/economist-explains-16>. Drum, Kevin. “The US Murder Rate Is on Track to Be Lowest in a Century.”Mother Jones. Mother Jones, 17 May 2013. Web. 13 Mar. 2015. <http://www.motherjones.com/kevin-drum/2013/05/us-murder-rate-track-be-lowest-century>. Hood, Roger, and Carolyn Hoyle. The Death Penalty: A Worldwide Perspective. Oxford: Oxford UP, 2002. 45. Print. Rizzo, Kevin. “Slideshow: America’s Safest and Most Dangerous States 2014.”Law Street Media. Law Street TM, 12 Sept. 2014. Web. 12 Mar. 2015. <http://lawstreetmedia.com/blogs/crime/safest-and-most-dangerous-states-2014/#slideshow>. Vollum, Scott. The Death Penalty: Constitutional Issues, Commentaries, and Case Briefs. Newark, NJ: LexisNexis, 2005. 2. Print. Theis, David. “Remarkable Declines in Global Poverty, But Major Challenges Remain.” The World Bank. The World Bank, 17 Apr. 2013. Web. 15 Mar. 2015. <http://www.worldbank.org/en/news/press-release/2013/04/17/remarkable-declines-in-global-poverty-but-major-challenges-remain>. Wilson, James Q. “Hard Times, Fewer Crimes.” WSJ. The Wall Street Journal, 28 May 2011. Web. 13 Mar. 2015. <http://www.wsj.com/articles/SB10001424052702304066504576345553135009870>.

Fact Debate Brief Introduction Crime doesn’t pay; it should be punished. Even since childhood, a slap on the hand has prevented possible criminals from ever committing the same offense; whether it was successful or not depended on how much that child wanted that cookie. While a slap on the wrist might or might not be an effective deterrent, the same can be said about the death penalty. Every day, somewhere in the world, a criminal is stopped permanently from committing any future costs, but this is by the means of the death. While effective in stopping one person permanently, it does nothing about the crime world as a whole. While it is necessary to end the career of a criminal, no matter what his or her crime is, we must not end it by taking a life. Through this paper, the death penalty will be proven ineffective at deterring crime by use of other environmental factors. Definition: The death penalty is defined as the universal punishment of death as legally applied by a fair court system. It is important for it to be a fair legal system, as not to confuse it with genocide, mob mentality, or any other ruling without trial. Claim 1: Use of the death penalty is in decline Ground 1: According to the book The Death Penalty: A Worldwide Perspective by Roger Hood and Carolyn Hoyle, published Dec. 8th, 2014, the Oxford professors in criminology say “As in most of the rest of the world, the death penalty in the US is in decline and distributed unevenly in frequency of use” even addressing that, as of April 2014, 18 states no longer have a death penalty, and even Oregon and Washington are considering removing their death penalty laws. Furthermore, in 2013, only 9 of these states still retaining the death penalty actually executed someone. Warrant 1: The death penalty can be reinstated at any time, but so far, it hasn’t been. At the same time, more states consider getting rid of it altogether. Therefore, it becomes clear that even states don’t want to be involved with this process showing that this is a disliked process. Claim 2: Even states with death penalty in effect still have high crime rates. Ground 2: With the reports gathered from fbi.gov, lawstreetmedia.com, a website based around political expertise and research determined the ranking of each state based on violent crime, published September 12th, 2014. Of the top ten most violent states, only three of which had the death penalty instituted (Maryland #9, New Mexico #4, Alaska #3). The other seven still had the system in place, and, despite it, still have a high amount of violent crime. On the opposite end of the spectrum, at the bottom ten most violent states, four of which, including the bottom-most states, do not have the death penalty in place. Warrant 2: With this ranking, it literally proves that the death penalty does not deter crime, or that there is a correlation between having the death penalty and having a decrease in the crime rate. Therefore, the idea of death penalty deterring crime is a null term in the sense that there is no, or a flawed connection. Claim 3: Violent crime is decreasing (but not because if the death penalty) Ground 3 A: According to an article published by The Economist, dated July 23rd, 2013, the rate of violent crime is in fact decreasing, but not because of the death penalty, but rather, because we have more police. From 1995 to 2010, policing has increased one-fifth, and with it, a decline in crime rate. In fact, in cities such as Detroit where policing has been cut, an opposite effect, an increase in crime, has been reported. Ground 3 B: An article from the Wall Street Journal, dated May 28th, 2011, also cites a decline in violent, only this time, citing the reason as a correlation with poverty levels. In 2009, at the start of the housing crisis, crime rates also dropped noticeably. Oddly enough, this article points out the belief that unemployment is often associated with crime; instead, the evidence presented is environmental in nature. Warrant 3: Crime rate isn’t deterred by death penalty, but rather, our surroundings. Seeing as how conditions have improved, so has the state of peace. Therefore, it becomes clear that the death penalty is ineffective at deterring crime because other key factors present more possibility for improvement of society. Claim 4: The death penalty is a historically flawed system. Ground 4A: According to the book The Death Penalty: Constitutional Issues, Commentaries, and Case Briefs by Scott Vollum, published in 2005, addresses how the case of the death penalty emerged to where it is today. While the book is now a decade old, it is used for historical context, particularly, in describing the first execution that took place in 1608. While it is true that most of these executions weren’t as well-grounded as the modern ones that take place now, they still had no effect in deterring crime. Why? Because even after America was established and more sane, the death penalty still had to be used because criminals still had violent behaviors. Ground 4B: According to data from Mother Jones, published May 17th, 2013, the reason why the crime rate was so high in the past could possibly be due to yet another environmental factor (affected by change over time), exposure to lead. Since the removal of lead from paint started over a hundred years ago, there has been a decline in homicide. Why is this important? Lead poisoning in child’s brain, if not lethal, can affect development and lead to mental disability, lower IQ, and lack of reasoning. Warrant 4: By examining history as a whole, there is a greater correlation between other factors that have resulted in a decline in violent crime. The decline in the crime rate has been an ongoing process, but has shown a faster decline due to other environmental factors, rather than the instatement of the death penalty. Claim 5: The world’s violent crime rate is changing, but not due to the death penalty. Ground 5A: According to article published by Amnesty USA in March of 2014, the number of executions under the death penalty reported in 2013 had increased by 15%. However, the rate of violent crime in the world has decreased significantly in the last decade. But, Latvia, for example, has permanently banned the death penalty since 2012. In 2014, the country was viewed overall as safe and low in violent crime rate. Ground 5B: However, while it is true that there is a decline in violent crime rate worldwide, The World Bank, April 17, 2013, reports that the rate of global poverty is decreasing. In a similar vein to the US, because wealth is being distributed better and conditions are improving overall, there is a steady decline in crime rate. Warrant 5: By examining the world as a whole, it becomes clear that it doesn’t matter if the death penalty is in place, violent crime will still exist. However, mirroring the US, as simple conditions improve, so does lifestyle. The death penalty does not deter crime in the world, rather a better quality of life is responsible for that. Works Cited “Death Sentences and Executions 2013.” Amnesty International USA. Amnesty USA, 26 Mar. 2014. Web. 15 Mar. 2015. . D. K. “Why Is Crime Falling?” The Economist. The Economist Newspaper, 23 July 2013. Web. 12 Mar. 2015. . Drum, Kevin. “The US Murder Rate Is on Track to Be Lowest in a Century.”Mother Jones. Mother Jones, 17 May 2013. Web. 13 Mar. 2015. . Hood, Roger, and Carolyn Hoyle. The Death Penalty: A Worldwide Perspective. Oxford: Oxford UP, 2002. 45. Print. Rizzo, Kevin. “Slideshow: America’s Safest and Most Dangerous States 2014.”Law Street Media. Law Street TM, 12 Sept. 2014. Web. 12 Mar. 2015. . Vollum, Scott. The Death Penalty: Constitutional Issues, Commentaries, and Case Briefs. Newark, NJ: LexisNexis, 2005. 2. Print. Theis, David. “Remarkable Declines in Global Poverty, But Major Challenges Remain.” The World Bank. The World Bank, 17 Apr. 2013. Web. 15 Mar. 2015. . Wilson, James Q. “Hard Times, Fewer Crimes.” WSJ. The Wall Street Journal, 28 May 2011. Web. 13 Mar. 2015. .

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Name: Lab Time: BIO 218 Experiment Paper Rubric (20 points) General Formatting: (2 pts.) • Margins should be 1 inch top, bottom, left, and right. • Font should be 12 point Times New Roman or similar font. • Double-spaced. • Pages numbered. Title page is unnumbered. Next page is numbered at the bottom right corner with a 2 followed by pages 3, 4, and 5. • All sections must be included: Abstract, Introduction, Methods, Results, Discussion, and Literature Cited. • At least 3 pages (double spaced) but no more than five pages long. • All scientific names should be formatted correctly by italicizing and capitalizing the genus name and having the species name in lowercase (Bufo americanus). • Title page should have a specific title, student name, course, lab section time, and date. Project elements (18 pts. Total) • Abstract (2 points) o Summarize most important points using past tense. Use present tense to suggest a general conclusion which supports or refutes the hypothesis. • Introduction (3 points) o General background on topic and species (state scientific name!) o Discuss the possible tests of the hypothesis. o Reads from general to specific. o States hypothesis/hypotheses to be addressed. May discuss null and all alternative hypotheses. • Methods (2 points) o Reports how experiment was conducted and all materials used. Use enough detail so others could repeat the study. o Discuss the type(s) of data collected. o Discuss how data was to be analyzed/compared/used to test hypothesis. • Results (3 points) o Reports what happened in the experiment. o If comparisons made, discuss how they were made. o Report statistical and other data. Use “significant” only for statistical significance. o NO interpretation of data (no data analysis). o At least one original figure present and formatted correctly. Figures such as pictures and graphs are numbered and have captions underneath. o At least one table present and formatted correctly. Tables such as charts are numbered and have captions above them. • Discussion: (3 points) o Discusses the results of the experiment and ties in how the results fit with the literature. o Use past tense to discuss your results and shift to present tense to discuss previously published information. o States how results supported or refuted the original hypothesis. Hypotheses are never proven! o Ties in results with big picture within topic of biology. • Literature Cited: (2 points: .5 per citation) o At least 2 peer-reviewed journal articles (provided) + 2 peer-reviewed journal articles (found on your own). o References used in text properly. o References all listed in this section are alphabetized by author’s last name and formatted correctly. o All references listed in the Literature Cited section are cited in text. Writing Elements (3 pts.) • Grammar or spelling is error-free and excellent print quality. (1 pt) • Writing is clear and flows logically throughout paper. (1 pt) • Appropriate content in each section? (1 pt) Additional Comments:

Name: Lab Time: BIO 218 Experiment Paper Rubric (20 points) General Formatting: (2 pts.) • Margins should be 1 inch top, bottom, left, and right. • Font should be 12 point Times New Roman or similar font. • Double-spaced. • Pages numbered. Title page is unnumbered. Next page is numbered at the bottom right corner with a 2 followed by pages 3, 4, and 5. • All sections must be included: Abstract, Introduction, Methods, Results, Discussion, and Literature Cited. • At least 3 pages (double spaced) but no more than five pages long. • All scientific names should be formatted correctly by italicizing and capitalizing the genus name and having the species name in lowercase (Bufo americanus). • Title page should have a specific title, student name, course, lab section time, and date. Project elements (18 pts. Total) • Abstract (2 points) o Summarize most important points using past tense. Use present tense to suggest a general conclusion which supports or refutes the hypothesis. • Introduction (3 points) o General background on topic and species (state scientific name!) o Discuss the possible tests of the hypothesis. o Reads from general to specific. o States hypothesis/hypotheses to be addressed. May discuss null and all alternative hypotheses. • Methods (2 points) o Reports how experiment was conducted and all materials used. Use enough detail so others could repeat the study. o Discuss the type(s) of data collected. o Discuss how data was to be analyzed/compared/used to test hypothesis. • Results (3 points) o Reports what happened in the experiment. o If comparisons made, discuss how they were made. o Report statistical and other data. Use “significant” only for statistical significance. o NO interpretation of data (no data analysis). o At least one original figure present and formatted correctly. Figures such as pictures and graphs are numbered and have captions underneath. o At least one table present and formatted correctly. Tables such as charts are numbered and have captions above them. • Discussion: (3 points) o Discusses the results of the experiment and ties in how the results fit with the literature. o Use past tense to discuss your results and shift to present tense to discuss previously published information. o States how results supported or refuted the original hypothesis. Hypotheses are never proven! o Ties in results with big picture within topic of biology. • Literature Cited: (2 points: .5 per citation) o At least 2 peer-reviewed journal articles (provided) + 2 peer-reviewed journal articles (found on your own). o References used in text properly. o References all listed in this section are alphabetized by author’s last name and formatted correctly. o All references listed in the Literature Cited section are cited in text. Writing Elements (3 pts.) • Grammar or spelling is error-free and excellent print quality. (1 pt) • Writing is clear and flows logically throughout paper. (1 pt) • Appropriate content in each section? (1 pt) Additional Comments:

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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.

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Vermont Technical College Electronic Applications ELT-2060 Lab 05: DC characteristics, input offset voltage and input bias current Reference: Operational Amplifiers with Linear Integrated Circuits Fourth edition William D. Stanley, pages 154-155 (Problems 3-21, 3-22 and Lab exercises LE 3-1 to LE 3-4) For the following exercises, make sure to record all calculations, estimations and measured results. Components: 2 741 Op Amps, 10k Ω Potentiometer, 4-10kΩ, 1kΩ , 100kΩ , 100Ω , 560kΩ , 5.6M Ω, resistors Objectives: a. Voltage offset Null Circuit and Closed-loop Differential Circuit b. Measurement of dc Input Offset Voltage c. Measurement of dc Bias and Offset Currents a. Voltage offset Null Circuit and Closed-loop Differential Circuit In this exercise, investigate the use of a null circuit to reduce the output dc offset to its minimum possible value. Refer to the “Voltage Offset Null Circuit” describe in the 741 op amp data sheet from Appendix C of your text book. Although there are no specific closed-loop configurations shown, use a closed-loop differential Amplifier shown in Figure 1. The differential nature of this type of circuit makes it particularly sensitive, therefore well suited, to illustrate the concept dc voltage offset. 1. Connect the closed-loop difference amplifier of Figure 1 with R=10k Ω and A=1. Using a 10kΩ potentiometer connect the “Voltage Offset Null Circuit” between nodes 1 and 5 as shown in the 741 data sheet. Keep in mind that a potentiometer is a three terminal device. You will need to connect the potentiometer wiper terminal to the lowest potential in the circuit -VCC. 2. Connect the two external circuit inputs (v1 and v2) to ground, measure the dc voltage. From the data sheet the expected value of offset voltage at room temperature is 2mV typical and 6mV maximum. Voltages at these levels will be hard to measure with the laboratory multimeter. 3. Adjust the potentiometer until the dc output magnitude is either zero or it’s minimum possible value. Record the minimum value of voltage attained. 5. Do not break down you difference amplifier. Next, build the non-inverting amplifier as shown in figure 2 with Ri=1k Ω and Rf =100k Ω. Attach the output of the difference amplifier to the input of the non-inverting amplifier. This will amplify your offset by 101. 6. Adjust the potentiometer until the dc output magnitude is either zero or it’s minimum possible value. Record the minimum value of voltage attained. 7. In effect we amplified the voltage offset from the difference amplifier by 101. Please describe any possible flaws in using this approach. Compare this result to what was measured in step 2. 8. Write an equation that expresses the expected output voltage Vo in terms of the two input voltages V1 and V2. 9. Apply dc input voltage for the following six combinations, compare the results to the expected values you calculate with the equation from step 8 a. V1=10V, V2=0V b. V1=0V, V2=10V c. V1=V2=10V d. V1=10mV, V2=0 e. V1=0, V2=10mV f. V1=V2=10mV b. Measurement of dc Input Offset Voltage ( Stanley Problem 3-21 page 151) A circuit and equation to measure the input offset voltage Vio is show in figure 3. With the proper selection of resistors Ri, Rf, and Rc the effects of offset due to input bias currents can be neglected. When the input terminals are both held to ground the resulting output voltage should be a direct measurement of Vio. 1. Build the circuit in Figure 3 with Ri=100 Ω and Rf=10k Ω measure and record Vo. Compare your results with the specification of input offset voltage provided in the data sheet. 2. Increase the value of Rf to 100k Ω, and measure Vo again. Did the output increase by approximately 10x the value recorded in step 1, if so explain how that validates the assumption the input bias currents are negligible. 3. Be sure to include a comparison of the measured values in steps 1 and 2. Include a discussion on how there relationship demonstrates that neglecting input bias current was a valid assumption. c. Measurement of dc Bias and Offset Currents (Stanley Problem 3-22 page 152) Consider the three circuits of figure 4 .The resistance R is chosen large so that the contribution to the output from bias currents is considerably larger than the contribution from the input offset voltages. The accompanying equations will predict the values of Ib+, Ib- and Iio. 1. Start with setting R=560k Ω and build each circuit in figure 4 one at a time. Going from one configuration to the next configuration should be quick, all that is changing is the placement of the resistors. Measure Voa, Vob and Voc for each circuit and calculate Ib+, Ib-, and Iio, compare your measurements to the values in the data sheet. 2. Increase the value of R to 5.6M Ω. Measure Voa, Vob and Voc for each circuit and calculate Ib+, Ib-, and Iio, compare your measurements to the values in the data sheet and to the results in part 1.Did the output increase by approximately 10x the value recorded in step 1, if so explain how that validates the assumption the input offset voltage effect is negligible. 3. Be sure to include a comparison of the measured values in steps 1 and 2. Include a discussion on why neglecting input offset voltage was a valid assumption. LAB write up: This lab requires a semi-formal lab report. Record all calculations, estimations, and measured results. No MultiSim will be required for this report. Please include a written English language paragraph for all lab steps that required an explanation.

Vermont Technical College Electronic Applications ELT-2060 Lab 05: DC characteristics, input offset voltage and input bias current Reference: Operational Amplifiers with Linear Integrated Circuits Fourth edition William D. Stanley, pages 154-155 (Problems 3-21, 3-22 and Lab exercises LE 3-1 to LE 3-4) For the following exercises, make sure to record all calculations, estimations and measured results. Components: 2 741 Op Amps, 10k Ω Potentiometer, 4-10kΩ, 1kΩ , 100kΩ , 100Ω , 560kΩ , 5.6M Ω, resistors Objectives: a. Voltage offset Null Circuit and Closed-loop Differential Circuit b. Measurement of dc Input Offset Voltage c. Measurement of dc Bias and Offset Currents a. Voltage offset Null Circuit and Closed-loop Differential Circuit In this exercise, investigate the use of a null circuit to reduce the output dc offset to its minimum possible value. Refer to the “Voltage Offset Null Circuit” describe in the 741 op amp data sheet from Appendix C of your text book. Although there are no specific closed-loop configurations shown, use a closed-loop differential Amplifier shown in Figure 1. The differential nature of this type of circuit makes it particularly sensitive, therefore well suited, to illustrate the concept dc voltage offset. 1. Connect the closed-loop difference amplifier of Figure 1 with R=10k Ω and A=1. Using a 10kΩ potentiometer connect the “Voltage Offset Null Circuit” between nodes 1 and 5 as shown in the 741 data sheet. Keep in mind that a potentiometer is a three terminal device. You will need to connect the potentiometer wiper terminal to the lowest potential in the circuit -VCC. 2. Connect the two external circuit inputs (v1 and v2) to ground, measure the dc voltage. From the data sheet the expected value of offset voltage at room temperature is 2mV typical and 6mV maximum. Voltages at these levels will be hard to measure with the laboratory multimeter. 3. Adjust the potentiometer until the dc output magnitude is either zero or it’s minimum possible value. Record the minimum value of voltage attained. 5. Do not break down you difference amplifier. Next, build the non-inverting amplifier as shown in figure 2 with Ri=1k Ω and Rf =100k Ω. Attach the output of the difference amplifier to the input of the non-inverting amplifier. This will amplify your offset by 101. 6. Adjust the potentiometer until the dc output magnitude is either zero or it’s minimum possible value. Record the minimum value of voltage attained. 7. In effect we amplified the voltage offset from the difference amplifier by 101. Please describe any possible flaws in using this approach. Compare this result to what was measured in step 2. 8. Write an equation that expresses the expected output voltage Vo in terms of the two input voltages V1 and V2. 9. Apply dc input voltage for the following six combinations, compare the results to the expected values you calculate with the equation from step 8 a. V1=10V, V2=0V b. V1=0V, V2=10V c. V1=V2=10V d. V1=10mV, V2=0 e. V1=0, V2=10mV f. V1=V2=10mV b. Measurement of dc Input Offset Voltage ( Stanley Problem 3-21 page 151) A circuit and equation to measure the input offset voltage Vio is show in figure 3. With the proper selection of resistors Ri, Rf, and Rc the effects of offset due to input bias currents can be neglected. When the input terminals are both held to ground the resulting output voltage should be a direct measurement of Vio. 1. Build the circuit in Figure 3 with Ri=100 Ω and Rf=10k Ω measure and record Vo. Compare your results with the specification of input offset voltage provided in the data sheet. 2. Increase the value of Rf to 100k Ω, and measure Vo again. Did the output increase by approximately 10x the value recorded in step 1, if so explain how that validates the assumption the input bias currents are negligible. 3. Be sure to include a comparison of the measured values in steps 1 and 2. Include a discussion on how there relationship demonstrates that neglecting input bias current was a valid assumption. c. Measurement of dc Bias and Offset Currents (Stanley Problem 3-22 page 152) Consider the three circuits of figure 4 .The resistance R is chosen large so that the contribution to the output from bias currents is considerably larger than the contribution from the input offset voltages. The accompanying equations will predict the values of Ib+, Ib- and Iio. 1. Start with setting R=560k Ω and build each circuit in figure 4 one at a time. Going from one configuration to the next configuration should be quick, all that is changing is the placement of the resistors. Measure Voa, Vob and Voc for each circuit and calculate Ib+, Ib-, and Iio, compare your measurements to the values in the data sheet. 2. Increase the value of R to 5.6M Ω. Measure Voa, Vob and Voc for each circuit and calculate Ib+, Ib-, and Iio, compare your measurements to the values in the data sheet and to the results in part 1.Did the output increase by approximately 10x the value recorded in step 1, if so explain how that validates the assumption the input offset voltage effect is negligible. 3. Be sure to include a comparison of the measured values in steps 1 and 2. Include a discussion on why neglecting input offset voltage was a valid assumption. LAB write up: This lab requires a semi-formal lab report. Record all calculations, estimations, and measured results. No MultiSim will be required for this report. Please include a written English language paragraph for all lab steps that required an explanation.

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BLY 101L – Take Home Assignment (20 pts. TOTAL) Due: Start of class time – Monday, June 30, 2014 OR Tuesday, July 1, 2014 1. Calculate the % of disks floating (%DF) for each time point and both Control and Treatment groups. (5 pts.) • refer to the class notes re: how to do this… 2. Neatly graph experimental results. (5 pts.) • graph paper • Microsoft Excel • refer to the class notes re: how to do this… 3. What was the overarching QUESTION addressed by the lab exercise? (1 pt.) 4. State “null” (H0) and “alternative” (HA) HYPOTHESES. (2 pts.) 5. State your PREDICTION in “If…., then…” format, based upon your knowledge of PS and as written in your lab guide. (1 pt.) 6. Applying what you’ve learned about photosynthesis… • Undoubtedly, you have heard mention of the effect of increasing concentrations of certain gasses (one of which is CO2) in Earth’s atmosphere, and its relevance to Climate Change. Sometime around two decades ago or so, plant scientists began to earnestly think about CO2 level and its effects on plant physiology and growth. Based upon your knowledge of photosynthesis and what you’ve learned from this week’s lab experiment… Formulate testable hypotheses (H0, HA) AND a prediction for this scenario. (3 pts.) • As a follow-on to the previous question and in the context of the experiment you performed in class…Aside from affecting “aesthetics” and habitat for fuzzy wuzzy animals, why are plant and conservation scientists worried about the effects of “clear cutting” (i.e., cutting down forests for development or other agricultural and industrial uses) in combination with rising CO2 levels? (NOTE: O2 HAS NOTHING TO DO WITH THE ANSWER TO THIS QUESTION…; 3 pts.) You MUST hand in the following: o Data table o Line graph of experimental results (plot both data sets on the SAME set of axes; see lecture notes) o Neatly typed answers to questions 3-6 REMEMBER: Images, written text AND/OR ideas are intellectual property and/or copyrighted! If you consult/borrow any published material (e.g., internet webpage text, published paper or report, your textbook, etc.) to construct answers to the questions above, you MUST CITE THE SOURCE FROM WHICH YOU COPIED THE IMAGES, TEXT or IDEAS. See below… Scientific Paper Chase, J. 2010. Stochastic community assembly causes higher biodiversity in more productive environments. Science 328: 1388-1391. Book Stein, B.A., Kutner, L.S., and Adams, J.S. 2000. Precious Heritage, The Status of Biodiversity in the United States. Oxford University Press, Oxford, England. Webpage NOAA, National Atmospheric and Oceanographic Administration. Accessed 01/05/12. http://www.nhc.noaa.gov/pastall.shtml#tracks_us.

BLY 101L – Take Home Assignment (20 pts. TOTAL) Due: Start of class time – Monday, June 30, 2014 OR Tuesday, July 1, 2014 1. Calculate the % of disks floating (%DF) for each time point and both Control and Treatment groups. (5 pts.) • refer to the class notes re: how to do this… 2. Neatly graph experimental results. (5 pts.) • graph paper • Microsoft Excel • refer to the class notes re: how to do this… 3. What was the overarching QUESTION addressed by the lab exercise? (1 pt.) 4. State “null” (H0) and “alternative” (HA) HYPOTHESES. (2 pts.) 5. State your PREDICTION in “If…., then…” format, based upon your knowledge of PS and as written in your lab guide. (1 pt.) 6. Applying what you’ve learned about photosynthesis… • Undoubtedly, you have heard mention of the effect of increasing concentrations of certain gasses (one of which is CO2) in Earth’s atmosphere, and its relevance to Climate Change. Sometime around two decades ago or so, plant scientists began to earnestly think about CO2 level and its effects on plant physiology and growth. Based upon your knowledge of photosynthesis and what you’ve learned from this week’s lab experiment… Formulate testable hypotheses (H0, HA) AND a prediction for this scenario. (3 pts.) • As a follow-on to the previous question and in the context of the experiment you performed in class…Aside from affecting “aesthetics” and habitat for fuzzy wuzzy animals, why are plant and conservation scientists worried about the effects of “clear cutting” (i.e., cutting down forests for development or other agricultural and industrial uses) in combination with rising CO2 levels? (NOTE: O2 HAS NOTHING TO DO WITH THE ANSWER TO THIS QUESTION…; 3 pts.) You MUST hand in the following: o Data table o Line graph of experimental results (plot both data sets on the SAME set of axes; see lecture notes) o Neatly typed answers to questions 3-6 REMEMBER: Images, written text AND/OR ideas are intellectual property and/or copyrighted! If you consult/borrow any published material (e.g., internet webpage text, published paper or report, your textbook, etc.) to construct answers to the questions above, you MUST CITE THE SOURCE FROM WHICH YOU COPIED THE IMAGES, TEXT or IDEAS. See below… Scientific Paper Chase, J. 2010. Stochastic community assembly causes higher biodiversity in more productive environments. Science 328: 1388-1391. Book Stein, B.A., Kutner, L.S., and Adams, J.S. 2000. Precious Heritage, The Status of Biodiversity in the United States. Oxford University Press, Oxford, England. Webpage NOAA, National Atmospheric and Oceanographic Administration. Accessed 01/05/12. http://www.nhc.noaa.gov/pastall.shtml#tracks_us.

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Statistical Methods (STAT 4303) Review for Final Comprehensive Exam Measures of Central Tendency, Dispersion Q.1. The data below represents the test scores obtained by students in college algebra class. 10,12,15,20,13,16,14 Calculate (a) Mean (b) Median (c) Mode (d) Variance, s2 (e) Coefficient of variation (CV) Q.2. The data below represents the test scores obtained by students in English class. 12,15,16,18,13,10,17,20 Calculate (a) Mean (b) Median (c) Mode (d) Variance, s2 (e) Coefficient of variation (CV) (f) Compare the results of Q.1 and Q.2, Which scores College Algebra or English do you think is more precise (less spread)? Q.3 Following data represents the score obtained by students in one of the exams 9, 13, 14, 15, 16, 16, 17, 19, 20, 21, 21, 22, 25, 25, 26 Create a frequency table to calculate the following descriptive statistics (a) mean (b) median (c) mode (d) first and third quartiles (e) Construct Box and Whisker plot. (f) Comment on the shape of the distribution. (g) Find inter quartile range (IQR). (h) Are there any outliers (based on IQR technique)? In the above problem, if the score 26 is replaced by 37 (i) What will happen to the mean? Will it increase, decrease or remains the same? (j) What will be the new median? (k) What can you say about the effect of outliers on mean and median? Q.4 Following data represents the score obtained by students in one of the exams 19, 14, 14, 15, 17, 16, 17, 20, 20, 21, 21, 22, 25, 25, 26, 27, 28 Create a frequency table to calculate the following descriptive statistics a) mean b) median c) mode d) first and third quartiles e) Construct Box and Whisker plot. f) Comment on the shape of the distribution. g) Find inter quartile range (IQR). h) Are there any outliers (based on IQR technique)? In the above problem, if the score 28 is replaced by 48 i) What will happen to the mean? Will it increase, decrease or remains the same? j) What will be the new median? k) What can you say about the effect of outliers on mean and median? Q.5 Consider the following data of height (in inch) and weight(in lbs). Height(x) Frequency 50 2 52 3 55 2 60 4 62 3  Find the mean height.  What is the variance of height? Also, find the standard deviation. (c) Find the coefficient of variation (CV). Q.6. The following table shows the number of miles run during one week for a sample of 20 runners: Miles Mid-value (x) Frequency (f) 5.5-10.5 1 10.5-15.5 2 15.5-20.5 3 20.5-25.5 5 25.5-30.5 4 (a) Find the average (mean) miles run. (Hint: Find mid-value of mile range first) (b) What is the variance of miles run? Also, find the standard deviation. (c) Find the coefficient of variation (CV). Q.7. (a) If the mean of 20 observations is 20.5, find the sum of all observations? (b) If the mean of 30 observations is 40, find the sum of all observations? Probability Q.8 Out of forty students, 14 are taking English Composition and 29 are taking Chemistry. a) How many students are in both classes? b) What is the probability that a randomly-chosen student from this group is taking only the Chemistry class? Q.9 A drawer contains 4 red balls, 5 green balls, and 5 blue balls. One ball is taken from the drawer and then replaced. Another ball is taken from the drawer. What is the probability that (Draw tree diagram to facilitate your calculation). (a) both balls are red (b) first ball is red (c) both balls are of same colors (d) both balls are of different colors (e) first ball is red and second ball is blue (f) first ball is red or blue Q.10 A drawer contains 3 red balls, 5 green balls, and 5 blue balls. One ball is taken from the drawer and not replaced. Another ball is then taken from the drawer. Draw tree diagram to facilitate your calculation. What is the probability that (a) both balls are red (b) first ball is red (c) both balls are of same colors (d) both balls are of different colors (e) first ball is red and second ball is blue (f) first ball is red or blue Q. 11 Missile A has 45% chance of hitting target. Missile B has 55% chance of hitting a target. What is the probability that (i) both miss the target. (ii) at least one will hit the target. (iii) exactly one will hit the target. Q. 12 A politician from D party speaks truth 65% of times; another politician from rival party speaks truth 75% of times. Both politicians were asked about their personal love affair with their own office secretary, what is the probability that (i) both lie the actual fact . (ii) at least one will speak truth. (iii) exactly one speaks the truth. (iv) both speak the truth. Q.13 The question, “Do you drink alcohol?” was asked to 220 people. Results are shown in the table. . Yes No Total Male 48 82 Female 24 66 Total (a) What is the probability of a randomly selected individual being a male also drinks? (b) What is the probability of a randomly selected individual being a female? (c) What is the probability that a randomly selected individual drinks? (d) A person is selected at random and if the person is female, what is the probability that she drinks? (e) What is the probability that a randomly selected alcoholic person is a male? Q.14 A professor, Dr. Drakula, taught courses that included statements from across the five colleges abbreviated as AH, AS, BA, ED and EN. He taught at Texas A&M University – Kingsville (TAMUK) during the span of five academic years AY09 to AY13. The following table shows the total number of graduates during AY09 to AY13. One day, he was running late to his class. He was so focused on the class that he did not stop for a red light. As soon as he crossed through the intersection, a police officer Asked him to stop. ( a ) It is turned out that the police officer was TAMUK graduate during the past five years. What is the probability that the Police Officer was from ED College? ( b ) What is the probability that the Police Officer graduated in the academic year of 2011? ( c ) If the traffic officer graduated from TAMUK in the academic year of 2011(AY11). What is the conditional probability that he graduated from the ED college? ( d ) Are the events the academic year “AY 11” and the college of Education “ED” independent? Yes or no , why? Discrete Distribution Q.15 Find k and probability for X=2 and X=4. X 1 2 3 4 5 P(X=x) 0.1 3k 0.2 2k 0.2 (Hint: First find k, and then plug in) Also, calculate the expected value of X, E(X) and variance V(X). A game plan is derived based on above table, a player wins $5 if he can blindly choose 3 and loses $1 if he chooses other numbers.What is his expected win or loss per game? If he plays this game for 20 times, what is total win or lose? Q.16 Find k. X 3 4 5 6 7 P(X=x) k 2k 2k k 2k (Hint: First find k, and then plug in) Also, calculate the expected value of X, E(X) and variance V(X). A game plan is derived based on above table, a player wins $5 if he can blindly choose 3 and loses $1 if he chooses other numbers. What is his expected win or loss per game? If he plays this game for 20 times, what is total win or lose? Binomial Distribution: Q.17 (a) Hospital records show that of patients suffering from a certain disease, 75% die of it. What is the probability that of 6 randomly selected patients, 4 will recover? (b) A (blindfolded) marksman finds that on the average he hits the target 4 times out of 5. If he fires 4 shots, what is the probability of (i) more than 2 hits? (ii) at least 3 misses? (c) which of the following are binomial experiments? Explain the reason. i. Telephone surveying a group of 200 people to ask if they voted for George Bush. ii. Counting the average number of dogs seen at a veterinarian’s office daily. iii. You take a survey of 50 traffic lights in a certain city, at 3 p.m., recording whether the light was red, green, or yellow at that time. iv. You are at a fair, playing “pop the balloon” with 6 darts. There are 20 balloons. 10 of the balloons have a ticket inside that say “win,” and 10 have a ticket that says “lose.” Normal Distribution Q.18 Use standard normal distribution table to find the following probabilities: (a) P(Z<2.5) (b) P(Z< -1.3) (c) P(Z>0.12) (d) P(Z> -2.15) (e) P(0.11<Z<0.22) (f) P(-0.11<Z<0.5) Q.19. Use normal distribution table to find the missing values (?). (a) P(Z< ?)=0.40 (b) P(Z< ?)=0.76 (c) P(Z> ?)=0.87 (d) P(Z> ?)=0.34 Q.20. The length of life of certain type of light bulb is normally distributed with mean=220hrs and standard deviation=20hrs. (a) Define a random variable, X A light bulb is randomly selected, what is the probability that (b) it will last will last more than 207 hrs. ? (c) it will last less than 214 hrs. (d) it will last in between 199 to 207 hrs. Q.21. The length of life of an instrument produced by a machine has a normal distribution with a mean of 22 months and standard deviation of 4 months. Find the probability that an instrument produced by this machine will last (a) less than 10 months. (b) more than 28 months (c) between 10 and 28 months. Distribution of sample mean and Central Limit Theorem (CLT) Q.22 It is assumed that weight of teenage student is normally distributed with mean=140 lbs. and standard deviation =15 lbs. A simple random sample of 40 teenage students is taken and sample mean is calculated. If several such samples of same size are taken (i) what could be the mean of all sample means. (ii) what could be the standard deviation of all sample means. (iii) will the distribution of sample means be normal ? (iv) What is CLT? Write down the distribution of sample mean in the form of ~ ( , ) 2 n X N   . Q.23 The time it takes students in a cooking school to learn to prepare seafood gumbo is a random variable with a normal distribution where the average is 3.2 hours and a standard deviation of 1.8 hours. A sample of 40 students was investigated. What is the distribution of sample mean (express in numbers)? Hypothesis Testing Q.24 The NCHS reported that the mean total cholesterol level in 2002 for all adults was 203 with standard deviation of 37. Total cholesterol levels in participants who attended the seventh examination of the Offspring in the Framingham Heart Study are summarized as follows: n=3,00, =200.3. Is there statistical evidence of a difference in mean cholesterol levels in the Framingham Offspring (means does the result form current examination differs from 2002 report)?? (Follow the steps below to reach the conclusion) (i) Define null and alternate hypothesis (Also write what is  , and x in words at the beginning) (ii) Identify the significance level ,  and check whether it is one sided or two sided test. (iii) Calculate test statistics, Z. (iv) Use standard normal table to find the p-value and state whether you reject or accept (fail to reject) the null hypothesis. (v) what is the critical value, do you reject or accept the H0. (vi) Write down the conclusion based on part (iv). Q.25 A sample of 145 boxes of Kellogg’s Raisin Bran contain in average 1.95 scoops of raisins. It is known from past experiments that the standard deviation for the number of scoops of raisins is 0.25. The manufacturer of Kellogg’s Raisin Bran claimed that in average their product contains more than 2 scoops of raisins, do you reject or accept the manufacturers claim (follow all five steps)? Q.26 It is assumed that the mean systolic blood pressure is μ = 120 mm Hg. In the Honolulu Heart Study, a sample of n = 100 people had an average systolic blood pressure of 130.1 mm Hg. The standard deviation from the population is 21.21 mm Hg. Is the group significantly different (with respect to systolic blood pressure!) from the regular population? Use 10% level of significance. Q.27 A CEO claims that at least 80 percent of the company’s 1,000,000 customers are very satisfied. Again, 100 customers are surveyed using simple random sampling. The result: 73 percent are very satisfied. Based on these results, should we accept or reject the CEO’s hypothesis? Assume a significance level of 0.05. Q.28 True/False questions (These questions are collected from previous HW, review and exam problems, see the previous solutions for answers) (a) Total sum of probability can exceed 1. (b) If you throw a die, getting 2 or any even number are independent events. (c) If you roll a die for 20 times, the probability of getting 5 in 15th roll is 20 15 . (d) A student is taking a 5 question True-False quiz but he has not been doing any work in the course and does not know the material so he randomly guesses at all the answers. Probability that he gets the first question right is 2 1 . (e) Typing in laptop and writing emails using the same laptop are independent events. (f) Normal distribution is right skewed. (g) Mean is more robust to outliers. So mean is used for data with extreme values. (h) It is possible to have no mode in the data. (i) Standard normal variable, Z has some unit. (j) Only two parameters are required to describe the entire normal distribution. (k) Mean of standard normal variable, Z is 1. (l) If p-value of more than level of significance (alpha), we reject the H0. (m) Very small p-value indicates rejection of H0. (n) H0 always contains equality sign. (o) CLT indicates that distribution of sample mean can be anything, not just normal. (p) Sample mean is always equal to population mean. (q) Variance of sample mean is less than population mean. (r) Variance of sample mean does not depend on sample size. (s) Mr. A has cancer but a medical doctor diagnosed him as “no cancer”. It is a type I error. (t) Level of significance is probability of making type II error. (u) Type II error can be controlled. (v) Type I error is more serious than type II error. (w) Type I and Type II errors are based on null hypothesis. Q.29 Type I and Type II Errors : Make statements about Type I (False Positive) and Type II errors (False Negative). (a) The Alpha-Fetoprotein (AFP) Test has both Type I and Type II error possibilities. This test screens the mother’s blood during pregnancy for AFP and determines risk. Abnormally high or low levels may indicate Down syndrome. (Hint: Take actual status as down syndrome or not) Ho: patient is healthy Ha: patient is unhealthy (b) The mechanic inspects the brake pads for the minimum allowable thickness. Ho: Vehicles breaks meet the standard for the minimum allowable thickness. Ha: Vehicles brakes do not meet the standard for the minimum allowable thickness. (c) Celiac disease is one of the diseases which can be misdiagnosed or have less diagnosis. Following table shows the actual celiac patients and their diagnosis status by medical doctors: Actual Status Yes No Diagnosed as celiac Yes 85 5 No 25 105 I. Calculate the probability of making type I and type II error rates. II. Calculate the power of the test. (Power of the test= 1- P(type II error) Answers: USEFUL FORMULAE: Descriptive Statistics Possible Outliers, any value beyond the range of Q 1.5( ) and Q 1.5( ) Range = Maximum value -Minimum value 100 where 1 ( ) (Preferred) 1 and , n fx x For data with repeats, 1 ( ) (Preferred ) OR 1 and n x x For data without repeats, 1 3 1 3 3 1 2 2 2 2 2 2 2 2 2 2 Q Q Q Q x s CV n f n f x x OR s n fx nx s n x x s n x nx s                             Discrete Distribution         ( ) ( ) ( ) ( ) { ( )} ( ) ( ) 2 2 2 2 E X x P X x V X E X E X E X xP X x Binomial Distribution Probability mass function, P(X=x)= x n x n x C p q  for x=0,1,2,…,n. E(X)=np, Var(X)=npq Hypothesis Testing based on Normal Distribution      X std X mean Z Standard Normal Variable, Probability Bayes Rule, ( ) ( and ) ( ) ( ) ( | ) P B P A B P B P A B P A B    Central Limit Theorem For large n (n>30), ~ ( , ) 2 n X N   and ˆ ~ ( , ) n pq p N p For hypothesis testing of μ, σ known           n x Z   For hypothesis testing of p n pq p p Z   ˆ ANSWERS: Q.1 (a) 14.286 (b) 14 (c) none (d) 10.24 (e) 22.40 Q.2 (a) 15.125 (b) 15.5 (c) No (d) 10.98 (e) 21.9 (f) English Q.3 (a) 18.6 (b)19 (c) 16, 21, and 25 (d) 15, 22 (f) slightly left (g) 7 (h) no outliers (i) increase (j) same Q.4 (a) 0.41 (b) 20 (c)14, 17, 20, 21,25 (d) 16.5, 25 (f) slightly right (g) 8.5 (h) no (i) increase (j) same Q.5 (a)56.57 (b) 22.26 (c) 8.34 Q.6 (a) 21 (b) 38.57 (c) 29.57 Q.7 (a) 410 (b) 1200 Q.8 (a)3 (b) 0.65 Q.9 (a) 0.082 (b) 0.29 (c)0.34 (d) 0.66 (e)0.10 (f) 0.64 Q.10 (a) 0.038 (b)0.23 (c) 0.71 (d) 0.29 (e)0.096 (f) 0.62 Q.11 (i)0.248 (ii)0.752 (iii)0.505 Q.12 (i)0.0875 (ii)0.913 (iii)0.425 (iii)0.488 Q.13 (a)0.22 (b)0.41 (c)0.33 (d)0.27 (e) 0.67 Q.14 (a) 0.13 (b) 0.18 (c)0.12 Q.15 E(X)=3.1 , V(X)=1.69, $0.2 per game, $ 4 win. Q.16 E(X)=5.125, V(X)=1.86, $0.25 loss per game, $5 loss. Q.17 (a)0.201 (b) 0.819, 0.027 Q.18 (a)0.9938 (b)0.0968 (c)0.452 (d)0.984 (e) 0.0433 (f)0.2353 Q.19 (a) -0.25 (b)0.71 (c) -1.13 (d)0.41 Q.20 (b) 0.7422 (c) 0.3821 (d) 0.1109 Q.21 (a)0.0014 (b) 0.0668 (c) 0.9318 Q.22 (a) 140 (b)2.37 Q.24 Z=-1.26, Accept null. Q.25 Z=-2.41, accept null Q.26 Z=4.76, reject H0 Q.27 Z=-1.75, reject H0 Q.28 F, F, F, T , F, F, F, T, F, T, F, F, T, T, F, F, T, F, T, F, F, T, T Q.29 (c)0.113 , 0.022 , 0.977 (or 98%)

Statistical Methods (STAT 4303) Review for Final Comprehensive Exam Measures of Central Tendency, Dispersion Q.1. The data below represents the test scores obtained by students in college algebra class. 10,12,15,20,13,16,14 Calculate (a) Mean (b) Median (c) Mode (d) Variance, s2 (e) Coefficient of variation (CV) Q.2. The data below represents the test scores obtained by students in English class. 12,15,16,18,13,10,17,20 Calculate (a) Mean (b) Median (c) Mode (d) Variance, s2 (e) Coefficient of variation (CV) (f) Compare the results of Q.1 and Q.2, Which scores College Algebra or English do you think is more precise (less spread)? Q.3 Following data represents the score obtained by students in one of the exams 9, 13, 14, 15, 16, 16, 17, 19, 20, 21, 21, 22, 25, 25, 26 Create a frequency table to calculate the following descriptive statistics (a) mean (b) median (c) mode (d) first and third quartiles (e) Construct Box and Whisker plot. (f) Comment on the shape of the distribution. (g) Find inter quartile range (IQR). (h) Are there any outliers (based on IQR technique)? In the above problem, if the score 26 is replaced by 37 (i) What will happen to the mean? Will it increase, decrease or remains the same? (j) What will be the new median? (k) What can you say about the effect of outliers on mean and median? Q.4 Following data represents the score obtained by students in one of the exams 19, 14, 14, 15, 17, 16, 17, 20, 20, 21, 21, 22, 25, 25, 26, 27, 28 Create a frequency table to calculate the following descriptive statistics a) mean b) median c) mode d) first and third quartiles e) Construct Box and Whisker plot. f) Comment on the shape of the distribution. g) Find inter quartile range (IQR). h) Are there any outliers (based on IQR technique)? In the above problem, if the score 28 is replaced by 48 i) What will happen to the mean? Will it increase, decrease or remains the same? j) What will be the new median? k) What can you say about the effect of outliers on mean and median? Q.5 Consider the following data of height (in inch) and weight(in lbs). Height(x) Frequency 50 2 52 3 55 2 60 4 62 3  Find the mean height.  What is the variance of height? Also, find the standard deviation. (c) Find the coefficient of variation (CV). Q.6. The following table shows the number of miles run during one week for a sample of 20 runners: Miles Mid-value (x) Frequency (f) 5.5-10.5 1 10.5-15.5 2 15.5-20.5 3 20.5-25.5 5 25.5-30.5 4 (a) Find the average (mean) miles run. (Hint: Find mid-value of mile range first) (b) What is the variance of miles run? Also, find the standard deviation. (c) Find the coefficient of variation (CV). Q.7. (a) If the mean of 20 observations is 20.5, find the sum of all observations? (b) If the mean of 30 observations is 40, find the sum of all observations? Probability Q.8 Out of forty students, 14 are taking English Composition and 29 are taking Chemistry. a) How many students are in both classes? b) What is the probability that a randomly-chosen student from this group is taking only the Chemistry class? Q.9 A drawer contains 4 red balls, 5 green balls, and 5 blue balls. One ball is taken from the drawer and then replaced. Another ball is taken from the drawer. What is the probability that (Draw tree diagram to facilitate your calculation). (a) both balls are red (b) first ball is red (c) both balls are of same colors (d) both balls are of different colors (e) first ball is red and second ball is blue (f) first ball is red or blue Q.10 A drawer contains 3 red balls, 5 green balls, and 5 blue balls. One ball is taken from the drawer and not replaced. Another ball is then taken from the drawer. Draw tree diagram to facilitate your calculation. What is the probability that (a) both balls are red (b) first ball is red (c) both balls are of same colors (d) both balls are of different colors (e) first ball is red and second ball is blue (f) first ball is red or blue Q. 11 Missile A has 45% chance of hitting target. Missile B has 55% chance of hitting a target. What is the probability that (i) both miss the target. (ii) at least one will hit the target. (iii) exactly one will hit the target. Q. 12 A politician from D party speaks truth 65% of times; another politician from rival party speaks truth 75% of times. Both politicians were asked about their personal love affair with their own office secretary, what is the probability that (i) both lie the actual fact . (ii) at least one will speak truth. (iii) exactly one speaks the truth. (iv) both speak the truth. Q.13 The question, “Do you drink alcohol?” was asked to 220 people. Results are shown in the table. . Yes No Total Male 48 82 Female 24 66 Total (a) What is the probability of a randomly selected individual being a male also drinks? (b) What is the probability of a randomly selected individual being a female? (c) What is the probability that a randomly selected individual drinks? (d) A person is selected at random and if the person is female, what is the probability that she drinks? (e) What is the probability that a randomly selected alcoholic person is a male? Q.14 A professor, Dr. Drakula, taught courses that included statements from across the five colleges abbreviated as AH, AS, BA, ED and EN. He taught at Texas A&M University – Kingsville (TAMUK) during the span of five academic years AY09 to AY13. The following table shows the total number of graduates during AY09 to AY13. One day, he was running late to his class. He was so focused on the class that he did not stop for a red light. As soon as he crossed through the intersection, a police officer Asked him to stop. ( a ) It is turned out that the police officer was TAMUK graduate during the past five years. What is the probability that the Police Officer was from ED College? ( b ) What is the probability that the Police Officer graduated in the academic year of 2011? ( c ) If the traffic officer graduated from TAMUK in the academic year of 2011(AY11). What is the conditional probability that he graduated from the ED college? ( d ) Are the events the academic year “AY 11” and the college of Education “ED” independent? Yes or no , why? Discrete Distribution Q.15 Find k and probability for X=2 and X=4. X 1 2 3 4 5 P(X=x) 0.1 3k 0.2 2k 0.2 (Hint: First find k, and then plug in) Also, calculate the expected value of X, E(X) and variance V(X). A game plan is derived based on above table, a player wins $5 if he can blindly choose 3 and loses $1 if he chooses other numbers.What is his expected win or loss per game? If he plays this game for 20 times, what is total win or lose? Q.16 Find k. X 3 4 5 6 7 P(X=x) k 2k 2k k 2k (Hint: First find k, and then plug in) Also, calculate the expected value of X, E(X) and variance V(X). A game plan is derived based on above table, a player wins $5 if he can blindly choose 3 and loses $1 if he chooses other numbers. What is his expected win or loss per game? If he plays this game for 20 times, what is total win or lose? Binomial Distribution: Q.17 (a) Hospital records show that of patients suffering from a certain disease, 75% die of it. What is the probability that of 6 randomly selected patients, 4 will recover? (b) A (blindfolded) marksman finds that on the average he hits the target 4 times out of 5. If he fires 4 shots, what is the probability of (i) more than 2 hits? (ii) at least 3 misses? (c) which of the following are binomial experiments? Explain the reason. i. Telephone surveying a group of 200 people to ask if they voted for George Bush. ii. Counting the average number of dogs seen at a veterinarian’s office daily. iii. You take a survey of 50 traffic lights in a certain city, at 3 p.m., recording whether the light was red, green, or yellow at that time. iv. You are at a fair, playing “pop the balloon” with 6 darts. There are 20 balloons. 10 of the balloons have a ticket inside that say “win,” and 10 have a ticket that says “lose.” Normal Distribution Q.18 Use standard normal distribution table to find the following probabilities: (a) P(Z<2.5) (b) P(Z< -1.3) (c) P(Z>0.12) (d) P(Z> -2.15) (e) P(0.11 ?)=0.87 (d) P(Z> ?)=0.34 Q.20. The length of life of certain type of light bulb is normally distributed with mean=220hrs and standard deviation=20hrs. (a) Define a random variable, X A light bulb is randomly selected, what is the probability that (b) it will last will last more than 207 hrs. ? (c) it will last less than 214 hrs. (d) it will last in between 199 to 207 hrs. Q.21. The length of life of an instrument produced by a machine has a normal distribution with a mean of 22 months and standard deviation of 4 months. Find the probability that an instrument produced by this machine will last (a) less than 10 months. (b) more than 28 months (c) between 10 and 28 months. Distribution of sample mean and Central Limit Theorem (CLT) Q.22 It is assumed that weight of teenage student is normally distributed with mean=140 lbs. and standard deviation =15 lbs. A simple random sample of 40 teenage students is taken and sample mean is calculated. If several such samples of same size are taken (i) what could be the mean of all sample means. (ii) what could be the standard deviation of all sample means. (iii) will the distribution of sample means be normal ? (iv) What is CLT? Write down the distribution of sample mean in the form of ~ ( , ) 2 n X N   . Q.23 The time it takes students in a cooking school to learn to prepare seafood gumbo is a random variable with a normal distribution where the average is 3.2 hours and a standard deviation of 1.8 hours. A sample of 40 students was investigated. What is the distribution of sample mean (express in numbers)? Hypothesis Testing Q.24 The NCHS reported that the mean total cholesterol level in 2002 for all adults was 203 with standard deviation of 37. Total cholesterol levels in participants who attended the seventh examination of the Offspring in the Framingham Heart Study are summarized as follows: n=3,00, =200.3. Is there statistical evidence of a difference in mean cholesterol levels in the Framingham Offspring (means does the result form current examination differs from 2002 report)?? (Follow the steps below to reach the conclusion) (i) Define null and alternate hypothesis (Also write what is  , and x in words at the beginning) (ii) Identify the significance level ,  and check whether it is one sided or two sided test. (iii) Calculate test statistics, Z. (iv) Use standard normal table to find the p-value and state whether you reject or accept (fail to reject) the null hypothesis. (v) what is the critical value, do you reject or accept the H0. (vi) Write down the conclusion based on part (iv). Q.25 A sample of 145 boxes of Kellogg’s Raisin Bran contain in average 1.95 scoops of raisins. It is known from past experiments that the standard deviation for the number of scoops of raisins is 0.25. The manufacturer of Kellogg’s Raisin Bran claimed that in average their product contains more than 2 scoops of raisins, do you reject or accept the manufacturers claim (follow all five steps)? Q.26 It is assumed that the mean systolic blood pressure is μ = 120 mm Hg. In the Honolulu Heart Study, a sample of n = 100 people had an average systolic blood pressure of 130.1 mm Hg. The standard deviation from the population is 21.21 mm Hg. Is the group significantly different (with respect to systolic blood pressure!) from the regular population? Use 10% level of significance. Q.27 A CEO claims that at least 80 percent of the company’s 1,000,000 customers are very satisfied. Again, 100 customers are surveyed using simple random sampling. The result: 73 percent are very satisfied. Based on these results, should we accept or reject the CEO’s hypothesis? Assume a significance level of 0.05. Q.28 True/False questions (These questions are collected from previous HW, review and exam problems, see the previous solutions for answers) (a) Total sum of probability can exceed 1. (b) If you throw a die, getting 2 or any even number are independent events. (c) If you roll a die for 20 times, the probability of getting 5 in 15th roll is 20 15 . (d) A student is taking a 5 question True-False quiz but he has not been doing any work in the course and does not know the material so he randomly guesses at all the answers. Probability that he gets the first question right is 2 1 . (e) Typing in laptop and writing emails using the same laptop are independent events. (f) Normal distribution is right skewed. (g) Mean is more robust to outliers. So mean is used for data with extreme values. (h) It is possible to have no mode in the data. (i) Standard normal variable, Z has some unit. (j) Only two parameters are required to describe the entire normal distribution. (k) Mean of standard normal variable, Z is 1. (l) If p-value of more than level of significance (alpha), we reject the H0. (m) Very small p-value indicates rejection of H0. (n) H0 always contains equality sign. (o) CLT indicates that distribution of sample mean can be anything, not just normal. (p) Sample mean is always equal to population mean. (q) Variance of sample mean is less than population mean. (r) Variance of sample mean does not depend on sample size. (s) Mr. A has cancer but a medical doctor diagnosed him as “no cancer”. It is a type I error. (t) Level of significance is probability of making type II error. (u) Type II error can be controlled. (v) Type I error is more serious than type II error. (w) Type I and Type II errors are based on null hypothesis. Q.29 Type I and Type II Errors : Make statements about Type I (False Positive) and Type II errors (False Negative). (a) The Alpha-Fetoprotein (AFP) Test has both Type I and Type II error possibilities. This test screens the mother’s blood during pregnancy for AFP and determines risk. Abnormally high or low levels may indicate Down syndrome. (Hint: Take actual status as down syndrome or not) Ho: patient is healthy Ha: patient is unhealthy (b) The mechanic inspects the brake pads for the minimum allowable thickness. Ho: Vehicles breaks meet the standard for the minimum allowable thickness. Ha: Vehicles brakes do not meet the standard for the minimum allowable thickness. (c) Celiac disease is one of the diseases which can be misdiagnosed or have less diagnosis. Following table shows the actual celiac patients and their diagnosis status by medical doctors: Actual Status Yes No Diagnosed as celiac Yes 85 5 No 25 105 I. Calculate the probability of making type I and type II error rates. II. Calculate the power of the test. (Power of the test= 1- P(type II error) Answers: USEFUL FORMULAE: Descriptive Statistics Possible Outliers, any value beyond the range of Q 1.5( ) and Q 1.5( ) Range = Maximum value -Minimum value 100 where 1 ( ) (Preferred) 1 and , n fx x For data with repeats, 1 ( ) (Preferred ) OR 1 and n x x For data without repeats, 1 3 1 3 3 1 2 2 2 2 2 2 2 2 2 2 Q Q Q Q x s CV n f n f x x OR s n fx nx s n x x s n x nx s                             Discrete Distribution         ( ) ( ) ( ) ( ) { ( )} ( ) ( ) 2 2 2 2 E X x P X x V X E X E X E X xP X x Binomial Distribution Probability mass function, P(X=x)= x n x n x C p q  for x=0,1,2,…,n. E(X)=np, Var(X)=npq Hypothesis Testing based on Normal Distribution      X std X mean Z Standard Normal Variable, Probability Bayes Rule, ( ) ( and ) ( ) ( ) ( | ) P B P A B P B P A B P A B    Central Limit Theorem For large n (n>30), ~ ( , ) 2 n X N   and ˆ ~ ( , ) n pq p N p For hypothesis testing of μ, σ known           n x Z   For hypothesis testing of p n pq p p Z   ˆ ANSWERS: Q.1 (a) 14.286 (b) 14 (c) none (d) 10.24 (e) 22.40 Q.2 (a) 15.125 (b) 15.5 (c) No (d) 10.98 (e) 21.9 (f) English Q.3 (a) 18.6 (b)19 (c) 16, 21, and 25 (d) 15, 22 (f) slightly left (g) 7 (h) no outliers (i) increase (j) same Q.4 (a) 0.41 (b) 20 (c)14, 17, 20, 21,25 (d) 16.5, 25 (f) slightly right (g) 8.5 (h) no (i) increase (j) same Q.5 (a)56.57 (b) 22.26 (c) 8.34 Q.6 (a) 21 (b) 38.57 (c) 29.57 Q.7 (a) 410 (b) 1200 Q.8 (a)3 (b) 0.65 Q.9 (a) 0.082 (b) 0.29 (c)0.34 (d) 0.66 (e)0.10 (f) 0.64 Q.10 (a) 0.038 (b)0.23 (c) 0.71 (d) 0.29 (e)0.096 (f) 0.62 Q.11 (i)0.248 (ii)0.752 (iii)0.505 Q.12 (i)0.0875 (ii)0.913 (iii)0.425 (iii)0.488 Q.13 (a)0.22 (b)0.41 (c)0.33 (d)0.27 (e) 0.67 Q.14 (a) 0.13 (b) 0.18 (c)0.12 Q.15 E(X)=3.1 , V(X)=1.69, $0.2 per game, $ 4 win. Q.16 E(X)=5.125, V(X)=1.86, $0.25 loss per game, $5 loss. Q.17 (a)0.201 (b) 0.819, 0.027 Q.18 (a)0.9938 (b)0.0968 (c)0.452 (d)0.984 (e) 0.0433 (f)0.2353 Q.19 (a) -0.25 (b)0.71 (c) -1.13 (d)0.41 Q.20 (b) 0.7422 (c) 0.3821 (d) 0.1109 Q.21 (a)0.0014 (b) 0.0668 (c) 0.9318 Q.22 (a) 140 (b)2.37 Q.24 Z=-1.26, Accept null. Q.25 Z=-2.41, accept null Q.26 Z=4.76, reject H0 Q.27 Z=-1.75, reject H0 Q.28 F, F, F, T , F, F, F, T, F, T, F, F, T, T, F, F, T, F, T, F, F, T, T Q.29 (c)0.113 , 0.022 , 0.977 (or 98%)

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