Facial structure of CEOS. In Psychological Science (Vol. 22, 2011), researchers reported that a chief executive officer's facial structure can be used to predict a firm's financial performance. The study involved measuring the facial width-to-height ratio (WHR) for each in a sample of 55 CEOS at publicly traded Fortune 500 firms. These WHR values (determined by computer analyzing a photo of the CEO's face) had a mean ofx = 1.96 and a standard deviation of s = .is. a. Find and interpret a 95% confidence interval for µ, the mean facial WHR for all CEOS at publicly traded Fortune 500 firms. b. The researchers found that CEOS with wider faces (relative to height) tended to be associated with firms that had greater financial performance. They based their inference on an equation that uses facial WHR to pre- dict financial performance. Suppose an analyst wants to predict the financial performance of a Fortune S00 firm based on the value of the true mean facial WHR of CEOS. The analyst wants to use the value of µ = 2.2. Do you recommend he use this value?

(3) The table contains hypothetical data from a study that a bank conducted on the credit card balances of male and female credit card holders (credit cards owned by both men and women were left out of the study). Male Female Mean $3,550 $2,670 Median $2,175 $2,500 Std Dev $1,240 $825 a. What conclusions can we come to by comparing the medians of the males and females? b. What conclusions can we come to by comparing the standard deviations of the males and females? c. Notice that the mean and median of the males are fairly far apart while the mean and median of the females are not. What does this tell us about the credit card balances of the males vs the credit card balances of the females?

An adventure company runs two obstacle courses, Fundash and Coolsprint. The designer of the courses suspects that the mean completion time of Fundash is not equal to the mean completion time of Coolsprint. To test this, she selects 240 Fundash runners and 200 Coolsprint runners. (Consider these as random samples of the Fundash and Coolspring runners.) The 240 Fundash runners complete the course with a mean time of 76.7 minutes and a standard deviation of 5.2 minutes. The 200 Coolsprint runners complete the course with a mean time of 77.5 minutes and a standard deviation of 5.4 minutes. Assume that the population standard deviations of the completion times can be estimated to be the sample standard deviations, since the samples that are used to compute them are quite large. At the 0.05 level of significance, is there enough evidence to support the claim that the mean completion time, μ1 , of Fundash is not equal to the mean completion time, μ2 , of Coolsprint?…

The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the average number of passing yards per attempt (Yds/Att) and the percentage of games won (WinPct) for a random sample of 10 NFL teams for the 2011 season (NFL website). Team Yds/Att WinPct 5.7 26 Arizona Cardinals Atlanta Falcons Carolina Panthers 7.6 67 7.3 52 6.9 51 Chicago Bears Dallas Cowboys 5.1 17 8.6 82 New England Patriots Philadelphia Eagles Seattle Seahawks 5.3 21 6.6 41 St. Louis Rams 6.5 41 Tampa Bay Buccaneers. 6.1 38 a. Choose the correct a scatter diagram with the number of passing yards per attempt on the horizontal axis and the percentage of games won on the vertical axis. B. A. WinPct WinPct 80 DD J F1 70- 60- 50+ -40- 30 20- F2 80 F3 000 000 F4 F5 80- -70 60- 50- 40- 30- 20- S F6 ● - F7 DII F8 F9 F10 () F11 <))) F12 A

The Wall Street Journal asked Concur Technologies, Inc., an expense management company, to examine data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city. The following table shows the average daily hotel room rate (*) and the average amount spent on entertainment (y) for a random sample of 9 of the 25 most-visited U.S. cities. These data lead to the estimated regression equation ŷ = 17.49 +1.0334x. For these data SSE = 1541.4. Click on the datafile logo to reference the data. Use Table 1 of Appendix B. DATA file City Boston Denver Nashville New Orleans Phoenix San Diego San Francisco San Jose Room Rate ($) 148 96 91 110 90 102 136 90 82 Tampa a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals). $ Entertainment ($) 161 105 101 142 ***** b. Develop a 95% confidence interval for the mean amount spent on…

The personality characteristics of business leaders (e.g., CEOS) are related to the operations of the businesses that they lead (Oreg & Berson, 2018). Traits like openness to experience are related to positive financial outcomes and other traits are related to negative financial outcomes for their businesses. Suppose that a board of directors is interested in evaluating the personality of their leadership. Among a sample of n = 16 managers, the sample mean of the openness to experiences dimension of personality was M = 4.50. Assuming that u = 4.24 and o = 1.05 (Cobb-Clark & Schurer, 2012), use a two-tailed hypothesis test with a = .05 to test the hypothesis that this company's business leaders' openness to experience is different from the population. Standard Normal Distribution Mean - 0.0 Standard Deviation 1.0 .7198 .1401 .1401 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 -1.08 1.08 Step 1. Ho: ; H;: a = .05. Step 2. The critical region consists of Step 3. For these data the standard error is and…

A study from 2014 found that adults in the US spend an average of 11 hours per day watching, reading, listening to or simply interacting with media. Researchers at UCLA suspect students spend less time engaging media. They grouped UCLA students by class section, randomly selected 20 class sections, and administered a survey to each student in those randomly selected class sections. The following data represents the mean time (in hours) per day spent engaging media for each of the randomly selected classes: 9.5 11.5 6.0 7.5 8 9.5 10.5 11 12 8.2 5 9.5 8.2 9.3 10.8 11 13 8.6 9.5 10.5 What would be the calculator steps to find standard deviaton, rounded to 3 decimal places?

A psychology student conducted a study on using a chief executive​ officer's facial structure to predict a​ firm's financial performance. The facial​ width-to-height ratio​ (WHR) for each in a sample of 55 CEOs at publicly traded firms was determined. The sample resulted in x=1.74 and s=2.02. The student wants to predict the financial performance of a firm based on the value of the true mean facial WHR of CEOs. The student wants to use the value of μ=2.3. Do you recommend he use this​ value? Conduct a test of hypothesis for μ to help you answer the question. Specify all the elements of the​ test, including H0​, Ha​, test​ statistic, p-value, and your conclusion. Test at α=0.10.   Find the​ p-value.   ​p-value=enter your response here ​(

An observational study of teams fishing for the red spiny lobster in a certain body of water was conducted and the results published in a science magazine. One of the variables of interest was the average distance separating traps - called "trap spacing" - deployed by the same team of fishermen. Trap spacing measurements (in meters) for a sample of seven teams of fishermen are shown in the accompanying table. Of interest is the mean trap spacing for the population of red spiny lobster fishermen fishing in this body of water. Complete parts a through f below. E Click the icon to view the trap spacing data. Trap Spacing Data a. Identify the target parameter for this study. The target parameter for this study is 93 101 107 95 81 68 84 b. Compute a point estimate of the target parameter. (Round to two decimal places as needed.) Print Done c. What is the problem with using the normal (z) statistic to finda confidence interval for the target parameter? O A. The point estimate is too large to…

A researcher is studying psychological factors in artistic achievement among teenage girls. One variable he is particularly interested in is perseverance. What information does a measure of variability for the variable perseverance convey? Check all that apply. What is the central tendency for the variable perseverance among teenage girls? What is the most common value for the variable perseverance among teenage girls? How spread out are the values for perseverance amoung teenage girls? Do all teenage girls have the same amount of perseverance?