6. Elon Corporation manufactures parts for an aircraft company. It uses a computerized numerical controlled (CNC) machining center to produce a specific part that has a design (nominal) target of 1.275 inches with tolerances of ±.024 inch. The CNC process that manufacturers these parts has a mean of 1.281 inches and a standard deviation of 0.008 inch. Determine the proportion of parts outside the specifications. Assume Normal Distribution.

6. Elon Corporation manufactures parts for an aircraft company. It uses a computerized numerical controlled (CNC) machining center to produce a specific part that has a design (nominal) target of 1.275 inches with tolerances of ±.024 inch. The CNC process that manufacturers these parts has a mean of 1.281 inches and a standard deviation of 0.008 inch. Determine the proportion of parts outside the specifications. Assume Normal Distribution.

P(defect) = P(X<1.251) + P(X>1.299) = P(X<1.251) +1- P(X<1.299) = … Read More...
CIV ENG 280 Computer-based Engineering Analysis Assignment for Lab 5 1. The number of annual precipitation days of one-half of the 50 largest U.S. cities is listed below. Find the mean, mode, median, range, standard deviation and variance of the data. 135 128 78 116 77 111 79 44 97 116 123 88 102 26 82 156 133 107 35 112 98 45 122 125 2. Please go through the steps described in the instruction manual (from page 112 to 136). Your lab report should include the following exercises in the manual. a) Binomial distribution (Page 112) b) Poisson distribution (page 119) c) Normal distribution (page 125) d) t distribution (page 132) 3. A math exam contains 10 multiple-choice questions, each with four choices. Since you have not spent any time preparing the exam, you decided to guess at each question by flipping a coin twice (i.e., two heads for A, head and tail for B, tail and head for C, two tails for D). Let X = the number of questions answered correctly. a) Plot the probability mass function (pmf) of the random variable X. (using the chart type “column”). b) If you have to get at least 5 questions answered correctly to pass the exam, what is the probability that you will pass.

CIV ENG 280 Computer-based Engineering Analysis Assignment for Lab 5 1. The number of annual precipitation days of one-half of the 50 largest U.S. cities is listed below. Find the mean, mode, median, range, standard deviation and variance of the data. 135 128 78 116 77 111 79 44 97 116 123 88 102 26 82 156 133 107 35 112 98 45 122 125 2. Please go through the steps described in the instruction manual (from page 112 to 136). Your lab report should include the following exercises in the manual. a) Binomial distribution (Page 112) b) Poisson distribution (page 119) c) Normal distribution (page 125) d) t distribution (page 132) 3. A math exam contains 10 multiple-choice questions, each with four choices. Since you have not spent any time preparing the exam, you decided to guess at each question by flipping a coin twice (i.e., two heads for A, head and tail for B, tail and head for C, two tails for D). Let X = the number of questions answered correctly. a) Plot the probability mass function (pmf) of the random variable X. (using the chart type “column”). b) If you have to get at least 5 questions answered correctly to pass the exam, what is the probability that you will pass.

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

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

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Distribution of the Sample Mean and Linear Combinations – Examples Example 1 Let X1;X2; : : : ;X100 denote the actual net weights of 100 randomly selected 50-pound bags of fertilizer. a. If the expected weight of each bag is 50 pounds and the standard deviation is 1 pound, approximate P(49:75 • ¹X • 50:25) using the CLT. b. If the expected weight is 49.8 pounds rather than 50 pounds, so that on average bags are under…lled, approximate P(49:75 • ¹X • 50:25). Example 2 The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 500 psi. a. What is the approximate probability that the sample mean breaking strength for a random sample of 40 rivets is between 9,900 psi and 10,200 psi? b. If the sample size had been 15 rivets rather than 40 rivets, could the probability requested in part a be approximated from the given information? Why or why not? Example 3 The lifetime of a certain type of battery is normally distributed with mean 8 hours and standard deviation 1 hour. There are four batteries in a package. What lifetime value is such that the total lifetime of all batteries in a package exceeds that value for only 5% of all packages? Example 4 Suppose your waiting time for a bus in the morning is uniformly distributed on [0; 5], while waiting time in the evening is uniformly distributed on [0; 10]. Assume that evening waiting time is independent of morning waiting time. a. If you take the bus each morning and evening for a week, what is your total expected waiting time. b. What is the variance of your total waiting time? expected value and variance of the di¤erence between morning and evening waiting time on a given day? d. What are the expected value and variance of the di¤erence between total morning waiting time and total evening waiting time for a particular week? 2 Example 5 Three di¤erent roads feed into a particular freeway entrance. Suppose that during a …xed time period, the number of cars coming from each road onto the freeway is a random variable, with expected value and standard deviation as given in the following table: Road 1 Road 2 Road 3 Expected Value 800 1000 600 Standard Deviation 16 25 18 : a. What is the expected total number of cars entering the freeway at this point during the period? b. What is the variance of the total number of entering cars? Have you made any assumptions about the relationship between the number of cars on the di¤erent roads? c. With Xi denoting the number of cars entering from road i during the period, suppose that Cov(X1;X2) = 80, Cov(X1;X3) = 90, and Cov(X2;X3) = 100 (so that the three streams of tra¢c are not independent). Compute the expected total number of entering cars and the standard deviation of the total. Example 6 In an area having sandy soil, 50 small trees of a certain type were planted, and another 50 trees were planted in an area having clay soil. Let X be the number of trees planted in sandy soil that survive one year and Y be the number of trees planted in clay soil that survive one year. If the probability that a tree planted in sandy soil will survive one year is 0.7 and the probability of one-year survival in clay soil is 0.6, compute an approximation to P(¡5 • X ¡ Y • 5). For the purposes of this exercise, ignore the continuity correction.

Distribution of the Sample Mean and Linear Combinations – Examples Example 1 Let X1;X2; : : : ;X100 denote the actual net weights of 100 randomly selected 50-pound bags of fertilizer. a. If the expected weight of each bag is 50 pounds and the standard deviation is 1 pound, approximate P(49:75 • ¹X • 50:25) using the CLT. b. If the expected weight is 49.8 pounds rather than 50 pounds, so that on average bags are under…lled, approximate P(49:75 • ¹X • 50:25). Example 2 The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 500 psi. a. What is the approximate probability that the sample mean breaking strength for a random sample of 40 rivets is between 9,900 psi and 10,200 psi? b. If the sample size had been 15 rivets rather than 40 rivets, could the probability requested in part a be approximated from the given information? Why or why not? Example 3 The lifetime of a certain type of battery is normally distributed with mean 8 hours and standard deviation 1 hour. There are four batteries in a package. What lifetime value is such that the total lifetime of all batteries in a package exceeds that value for only 5% of all packages? Example 4 Suppose your waiting time for a bus in the morning is uniformly distributed on [0; 5], while waiting time in the evening is uniformly distributed on [0; 10]. Assume that evening waiting time is independent of morning waiting time. a. If you take the bus each morning and evening for a week, what is your total expected waiting time. b. What is the variance of your total waiting time? expected value and variance of the di¤erence between morning and evening waiting time on a given day? d. What are the expected value and variance of the di¤erence between total morning waiting time and total evening waiting time for a particular week? 2 Example 5 Three di¤erent roads feed into a particular freeway entrance. Suppose that during a …xed time period, the number of cars coming from each road onto the freeway is a random variable, with expected value and standard deviation as given in the following table: Road 1 Road 2 Road 3 Expected Value 800 1000 600 Standard Deviation 16 25 18 : a. What is the expected total number of cars entering the freeway at this point during the period? b. What is the variance of the total number of entering cars? Have you made any assumptions about the relationship between the number of cars on the di¤erent roads? c. With Xi denoting the number of cars entering from road i during the period, suppose that Cov(X1;X2) = 80, Cov(X1;X3) = 90, and Cov(X2;X3) = 100 (so that the three streams of tra¢c are not independent). Compute the expected total number of entering cars and the standard deviation of the total. Example 6 In an area having sandy soil, 50 small trees of a certain type were planted, and another 50 trees were planted in an area having clay soil. Let X be the number of trees planted in sandy soil that survive one year and Y be the number of trees planted in clay soil that survive one year. If the probability that a tree planted in sandy soil will survive one year is 0.7 and the probability of one-year survival in clay soil is 0.6, compute an approximation to P(¡5 • X ¡ Y • 5). For the purposes of this exercise, ignore the continuity correction.

How do differences of culture between countries or within a country affect the operations of your chosen organization or of firms in your chosen industry sector? (10 marks) UNIT 5.The Socio-Cultural Environment Elements of culture: language, religion, values, customs, education, diversity.cultural changesBusiness ethics and the concept of corporate social responsibility.Aging or age distribution, population size changes, demographic changes, ethical argument in favour of CSR

How do differences of culture between countries or within a country affect the operations of your chosen organization or of firms in your chosen industry sector? (10 marks) UNIT 5.The Socio-Cultural Environment Elements of culture: language, religion, values, customs, education, diversity.cultural changesBusiness ethics and the concept of corporate social responsibility.Aging or age distribution, population size changes, demographic changes, ethical argument in favour of CSR

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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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Faraday’s Law of Induction 1a. Problem 28.9 b. Problem 28.39 2. Problem 28.43 3. Problem 28.71 Inductance 4a. Problem 28.56 b. Estimate the magnetic energy stored in the first kilometer of atmosphere above Milwaukee. Compare your answer to the energy stored in a 15-gallon gas tank. ugasoline=120 M J/gal 5. Problem 28.65 Feel free to sketch by hand, rather than using a “spreadsheet program.” 6a. Problem 29.83 (From the next chapter!) b. If the power delivered to the residents is 20kW, how much current flows on either side of the transformer? c. The 2000-volt distribution lines have a total resistance of 3Ω, how much power is lost as thermal dissipation? How much would be lost if those same lines operated at 240V? Hint: Use your answers from part b to calculate the powers in part c… EC1: Problem 28.53 EC2: Problem 28.80

Faraday’s Law of Induction 1a. Problem 28.9 b. Problem 28.39 2. Problem 28.43 3. Problem 28.71 Inductance 4a. Problem 28.56 b. Estimate the magnetic energy stored in the first kilometer of atmosphere above Milwaukee. Compare your answer to the energy stored in a 15-gallon gas tank. ugasoline=120 M J/gal 5. Problem 28.65 Feel free to sketch by hand, rather than using a “spreadsheet program.” 6a. Problem 29.83 (From the next chapter!) b. If the power delivered to the residents is 20kW, how much current flows on either side of the transformer? c. The 2000-volt distribution lines have a total resistance of 3Ω, how much power is lost as thermal dissipation? How much would be lost if those same lines operated at 240V? Hint: Use your answers from part b to calculate the powers in part c… EC1: Problem 28.53 EC2: Problem 28.80

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Use the link provided to answer the questions below. http://www.worlddialogue.org/content.php?id=384 According to the article, what was President George W. Bush’s main rationale for going to war with Iraq? A. Bush believed that by promoting democracy, we promote peace around the world. B. Bush believed that Iraq was a key player in the global drug trade. C. Bush feared Osama bin Laden would assume power in Iraq. D. Intelligence reports showed Iraq was planning to attack Afghanistan. E. Bush had no opinion about invading Iraq. What is the democratic peace theory? A. the theory that indicates that democracy will inevitably spread and we should assist it peacefully B. the theory that economic growth leads to a peaceful democratic state C. the theory that democracies tend not to fight one another D. the theory that the key to a successful democratic transition is through a peaceful transfer of power E. the theory that peace and democracy are actually inconsistent with one another What did Mansfield and Syder conclude happens during the initial phases of democratization? A. Newly democratized countries are incapable of holding independent elections. B. Citizens are more engaged in politics and willing to be peaceful. C. New democracies are the strongest democracies in the world. D. Other countries are more likely to form alliances with new democracies. E. Newly democratized countries become more aggressive and warlike, not less. New democracies are more likely to elect which of the following types of parties into office? A. socialists B. religious extremists C. the country’s elite and wealthy class D. people who personify “the average Joe” E. the largest, most prominent parties According to Mansfield and Snyder’s prescription, what should the United States do with democratizing states? A. provide an international military force to ensure peace B. keep a close eye and replace bad leaders if necessary C. make certain that reforms are implemented in the right order D. strengthen international awareness of democratizing states so that peaceful states can arm themselves E. attempt to push through elections as soon as possible above all else Watch the video below, and then answer the questions below. To save your answers, click the Save to Notebook button above. http://www.youtube.com/watch?v=796LfXwzIUk According to Joseph Nye, what is power transition? A. a change of power among states B. a change of power among presidents C. a change of power within the European Union or other leading organizations D. a change of power within cultures E. a change of power to non-state actors How does Nye define power diffusion? A. a change of power among states B. a change of power in regions C. a change of power within cultures D. a change of power from states to non-state actors E. a change of power from non-state actors to states Which of the following is an example of a non-state actor given by Nye? A. Iranian president Mahmoud Ahmadinejad B. Oxfam C. the former USSR D. socialism E. the mayor of Tehran Why does Nye claim it is important to be cautious of power projections? A. Simple projections don’t tell us much about power transition. B. History is not linear. C. Simple projections tend to focus soley on GDP. D. Simple projections don’t tell you anything about military or soft power. E. all of these options Nye describes a three-dimensional chess game as a metaphor for modern-day power distribution. What is the top board? A. economic power among states B. military power among states C. power among state leaders D. the deciding board for the other two boards E. the board where Kasparov faces off against the computer What is the middle board in Nye’s chess game metaphor? A. non-state actors B. a metaphor for the international underground economy C. military power among states D. economic power among states E. political power among states What is the bottom board in Nye’s chess game metaphor? A. transnational relations B. things that cross borders outside government control C. a place where power is chaotically distributed D. an area where things cross borders outside the control of governments E. all of these options What is the difference between a positive-sum game and a zero-sum game? A. A positive-sum game is when one person has all the power and a zero-sum game is when power is evenly distributed. B. A positive-sum game is a two-player power game and a zero-sum game is a one-player power game. C. A positive-sum game where my gain is your gain and a zero-sum game is my win and your loss. D. A postive-sum game is when you bet and win and a zero-sum game is when you bet and lose. E. A positive-sum game is like Tetris and a zero-sum game is like Super Mario Brothers. Nye quotes Hillary Clinton, describing her foreign policy agenda as utilizing “smart power.” What does this mean? A. Smart power addresses the two great power shifts in the 21st century. B. Smart power is “using all the tools in our toolbox.” C. Smart power combines both hard and soft power. D. Smart power reflects a new narrative of dealing with power. E. all of these options

Use the link provided to answer the questions below. http://www.worlddialogue.org/content.php?id=384 According to the article, what was President George W. Bush’s main rationale for going to war with Iraq? A. Bush believed that by promoting democracy, we promote peace around the world. B. Bush believed that Iraq was a key player in the global drug trade. C. Bush feared Osama bin Laden would assume power in Iraq. D. Intelligence reports showed Iraq was planning to attack Afghanistan. E. Bush had no opinion about invading Iraq. What is the democratic peace theory? A. the theory that indicates that democracy will inevitably spread and we should assist it peacefully B. the theory that economic growth leads to a peaceful democratic state C. the theory that democracies tend not to fight one another D. the theory that the key to a successful democratic transition is through a peaceful transfer of power E. the theory that peace and democracy are actually inconsistent with one another What did Mansfield and Syder conclude happens during the initial phases of democratization? A. Newly democratized countries are incapable of holding independent elections. B. Citizens are more engaged in politics and willing to be peaceful. C. New democracies are the strongest democracies in the world. D. Other countries are more likely to form alliances with new democracies. E. Newly democratized countries become more aggressive and warlike, not less. New democracies are more likely to elect which of the following types of parties into office? A. socialists B. religious extremists C. the country’s elite and wealthy class D. people who personify “the average Joe” E. the largest, most prominent parties According to Mansfield and Snyder’s prescription, what should the United States do with democratizing states? A. provide an international military force to ensure peace B. keep a close eye and replace bad leaders if necessary C. make certain that reforms are implemented in the right order D. strengthen international awareness of democratizing states so that peaceful states can arm themselves E. attempt to push through elections as soon as possible above all else Watch the video below, and then answer the questions below. To save your answers, click the Save to Notebook button above. http://www.youtube.com/watch?v=796LfXwzIUk According to Joseph Nye, what is power transition? A. a change of power among states B. a change of power among presidents C. a change of power within the European Union or other leading organizations D. a change of power within cultures E. a change of power to non-state actors How does Nye define power diffusion? A. a change of power among states B. a change of power in regions C. a change of power within cultures D. a change of power from states to non-state actors E. a change of power from non-state actors to states Which of the following is an example of a non-state actor given by Nye? A. Iranian president Mahmoud Ahmadinejad B. Oxfam C. the former USSR D. socialism E. the mayor of Tehran Why does Nye claim it is important to be cautious of power projections? A. Simple projections don’t tell us much about power transition. B. History is not linear. C. Simple projections tend to focus soley on GDP. D. Simple projections don’t tell you anything about military or soft power. E. all of these options Nye describes a three-dimensional chess game as a metaphor for modern-day power distribution. What is the top board? A. economic power among states B. military power among states C. power among state leaders D. the deciding board for the other two boards E. the board where Kasparov faces off against the computer What is the middle board in Nye’s chess game metaphor? A. non-state actors B. a metaphor for the international underground economy C. military power among states D. economic power among states E. political power among states What is the bottom board in Nye’s chess game metaphor? A. transnational relations B. things that cross borders outside government control C. a place where power is chaotically distributed D. an area where things cross borders outside the control of governments E. all of these options What is the difference between a positive-sum game and a zero-sum game? A. A positive-sum game is when one person has all the power and a zero-sum game is when power is evenly distributed. B. A positive-sum game is a two-player power game and a zero-sum game is a one-player power game. C. A positive-sum game where my gain is your gain and a zero-sum game is my win and your loss. D. A postive-sum game is when you bet and win and a zero-sum game is when you bet and lose. E. A positive-sum game is like Tetris and a zero-sum game is like Super Mario Brothers. Nye quotes Hillary Clinton, describing her foreign policy agenda as utilizing “smart power.” What does this mean? A. Smart power addresses the two great power shifts in the 21st century. B. Smart power is “using all the tools in our toolbox.” C. Smart power combines both hard and soft power. D. Smart power reflects a new narrative of dealing with power. E. all of these options

Use the link provided to answer the questions below. http://www.worlddialogue.org/content.php?id=384 … Read More...
Instructions 1. The next sheet is an example problem from the text. Select the cells at the top of the columns to see the formulas and format. 2. Columns A,B, and C are the input data. Note that the upper boundary is used. Columns D and E are used to calculate the average and sample standard deviation. Column F calculates the z value using the upper boundary (Column B), the average, and the sample standard deviation. Column G is the area (cumulative probability) under the normal curve to the left of the z value in the same manner as Table A. Column H is the area [probability] for each cell. Note that the formula for Row 3 is different than the rest of the rows. Column I is the expected frequency for each cell. It equals the value in Column H times the total number of observed values (110). Column J is the chi-squared value which can be compared to a chi-squared table to determine the observed values (110). This column is really not necessary because the program calculates the observed values (110) and performs the chi-squared test at I21 and K21. Column K is an adjustment to bring the total number of observed values to 110. The chi-squared test for the adjustment gives a probability of 0.971that the distribution is normal. 3. The following sheet, called template, should be copied before using the program. This activity is accomplished by selecting EDIT, selecting MOVE OR COPY SHEET, selecting CREATE A COPY, and locating the new sheet, called template (2), in the dialog box. 4. The template is designed for 9 cells. If more or less cells are required, the appropriate changes must be made.

Instructions 1. The next sheet is an example problem from the text. Select the cells at the top of the columns to see the formulas and format. 2. Columns A,B, and C are the input data. Note that the upper boundary is used. Columns D and E are used to calculate the average and sample standard deviation. Column F calculates the z value using the upper boundary (Column B), the average, and the sample standard deviation. Column G is the area (cumulative probability) under the normal curve to the left of the z value in the same manner as Table A. Column H is the area [probability] for each cell. Note that the formula for Row 3 is different than the rest of the rows. Column I is the expected frequency for each cell. It equals the value in Column H times the total number of observed values (110). Column J is the chi-squared value which can be compared to a chi-squared table to determine the observed values (110). This column is really not necessary because the program calculates the observed values (110) and performs the chi-squared test at I21 and K21. Column K is an adjustment to bring the total number of observed values to 110. The chi-squared test for the adjustment gives a probability of 0.971that the distribution is normal. 3. The following sheet, called template, should be copied before using the program. This activity is accomplished by selecting EDIT, selecting MOVE OR COPY SHEET, selecting CREATE A COPY, and locating the new sheet, called template (2), in the dialog box. 4. The template is designed for 9 cells. If more or less cells are required, the appropriate changes must be made.

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