MBA 624 Week 8 Quiz Questions and Answers/100% Correct/Homework Chapter 8 Test

MBA 624 Week 8 Quiz Questions and Answers/100% Correct/Homework Chapter 8 Test MBA 624 Week 8 Quiz Questions and Answers/100% Correct/Homework Chapter 8 Test Question 1 A correlation analysis requires that the data be either data or data. nominal, ratio interval, ratio ordinal, interval nominal, interval Question 2 Consider the relationship between the following variables: ∙ Monthly electricity bill for a household during the summer ∙ Average high ambient temperature during the summer months Average high ambient temperature during the summer months would be considered the dependent variable. True False Question 3 Costco sells paperback books in their retail stores and wanted to examine the relationship between price and demand. The price of a particular novel was adjusted each week and the weekly sales were recorded in the table below. Sales Price 3 $12 4 $11 6 $10 10 $9 8 $8 10 $7 The correlation coefficient for this data is . -0.402 -0.910 -0.623 0.197 Question 4 Costco sells paperback books in their retail stores and wanted to examine the relationship between price and demand. The price of a particular novel was adjusted each week and the weekly sales were recorded in the table below. Sales Price 3 $12 4 $11 6 $10 10 $9 8 $8 10 $7 Management would like to use simple regression analysis to estimate weekly demand for this novel using the price of the novel. The slope for the regression equation is . -0.920 -0.584 -0.675 -1.457 Question 5 Costco sells paperback books in their retail stores and wanted to examine the relationship between price and demand. The price of a particular novel was adjusted each week and the weekly sales were recorded in the table below. Sales Price 3 $12 4 $11 6 $10 10 $9 8 $8 10 $7 Management would like to use simple regression analysis to estimate weekly demand for this novel using the price of the novel. The average weekly sales for the novel when priced at $9 is . 6.22 5.32 4.70 7.56 Question 6 Costco sells paperback books in their retail stores and wanted to examine the relationship between price and demand. The price of a particular novel was adjusted each week and the weekly sales were recorded in the table below. Sales Price 3 $12 4 $11 6 $10 10 $9 8 $8 10 $7 Management would like to use simple regression analysis to estimate weekly demand for this novel using the price of the novel. The coefficient of determination for this sample is . 0.881 0.624 0.336 0.830 Question 7 Sarah is the office manager for a group of financial advisors who provide financial services for individual clients. She would like to investigate whether a relationship exists between the number of presentations made to prospective clients in a month and the number of new clients per month. The following table shows the number of presentations and corresponding new clients for a random sample of six employees. Employee Presentations New Clients 1 7 2 2 9 3 3 9 4 4 10 3 5 11 5 6 12 3 Sarah would like to use simple regression analysis to estimate the number of new clients per month based on the number of presentations made by the employee per month. The slope for the regression equation is . 0.8750 0.3043 0.1553 0.5987 Question 8 Sarah is the office manager for a group of financial advisors who provide financial services for individual clients. She would like to investigate whether a relationship exists between the number of presentations made to prospective clients in a month and the number of new clients per month. The following table shows the number of presentations and corresponding new clients for a random sample of six employees. Employee Presentations New Clients 1 7 2 2 9 3 3 9 4 4 10 3 5 11 5 6 12 3 Sarah would like to use simple regression analysis to estimate the number of new clients per month based on the number of presentations made by the employee per month. The y-intercept for the regression equation is . 2.4510 6.7500 4.9825 0.3913 Question 9 Sarah is the office manager for a group of financial advisors who provide financial services for individual clients. She would like to investigate whether a relationship exists between the number of presentations made to prospective clients in a month and the number of new clients per month. The following table shows the number of presentations and corresponding new clients for a random sample of six employees. Employee Presentations New Clients 1 7 2 2 9 3 3 9 4 4 10 3 5 11 5 6 12 3 Sarah would like to use simple regression analysis to estimate the number of new clients per month based on the number of presentations made by the employee per month. The average number of new clients per month for an employee who made 10 presentations per month is . 2.39 3.05 3.43 1.67 Question 10 The indicates both the strength and direction of the linear relationship between the independent and dependent variables. regression intercept coefficient of determination regression slope correlation coefficient Question 11 The is used to test the significance of the population coefficient of determination. chi-square distribution Student's t-distribution F-distribution normal distribution Question 12 The measures the amount of dispersion of observed data around a regression line. coefficient of determination correlation coefficient standard error of the slope standard error of the estimate Question 13 The measures how consistent the slope of the regression equation would be if several sets of samples from the population were selected and the regression equation were derived for each of them. correlation coefficient coefficient of determination standard error of the slope standard error of the estimate Question 14 Two variables have a correlation coefficient equal to -0.65 from a sample size of 10. Which one of the following statements describes the results of the hypothesis test that the population correlation coefficient is less than zero using α = 0.05? Because the test statistic is less than the critical value, we can reject the null hypothesis and conclude that the population correlation coefficient is not less than zero. Because the test statistic is greater than the critical value, we fail to reject the null hypothesis and conclude that the population correlation coefficient is not less than zero. Because the test statistic is less than the critical value, we can reject the null hypothesis and conclude that the population correlation coefficient is less than zero. Because the test statistic is greater than the critical value, we can reject the null hypothesis and conclude that the population correlation coefficient is less than zero. Question 15 Use the information below to answer the following question(s). Cape May Realty manages rental beach properties during the summer season for property owners. They would like to determine if a relationship exists between the square footage of beach property and the weekly rental rates during the summer season. Simple regression analysis was performed using a random sample of beach properties with the results shown below. According to these regression results, the average weekly rental for a property that is 2,000 square feet is . $1,750 $1,598 $1,473 $1,219 Question 16 Use the information below to answer the following question(s). Cape May Realty manages rental beach properties during the summer season for property owners. They would like to determine if a relationship exists between the square footage of beach property and the weekly rental rates during the summer season. Simple regression analysis was performed using a random sample of beach properties with the results shown below. The percentage of the variation in weekly rental that is explained by the square footage of the property is . 22.45 15.99 52.58 47.38 Question 17 Use the information below to answer the following question(s). C would like to use simple regression to predict the selling price of a used car, in thousands of dollars, based on the age of the car in years. A random sample of used cars was selected and the result of the regression analysis is shown below. Which one of the following statements is true using α = 0.05? Because the p-value for the slope is 0.0002, we fail to reject the null hypothesis and conclude that there is a relationship between the age and selling price of a used car. Because the p-value for the slope is 0.0351, we can reject the null hypothesis and conclude that there is no relationship between the age and selling price of a used car. Because the p-value for the slope is 0.0002, we can reject the null hypothesis and conclude that there is a relationship between the age and selling price of a used car. Because the p-value for the slope is 0.0351, we can reject the null hypothesis and conclude that there is a relationship between the age and selling price of a used car. Question 18 TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: Referring to table 13-11, which of the following is the correct interpretation for the slope coefficient? For each decrease of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. For each increase of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. For each decrease of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands. For each increase of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands. Question 19 Assuming a linear relationship between X and Y, if the coefficient of correlation (r) equals -0.30, there is no correlation. the slope (b1) is negative. variable X is larger than variable Y. the variance of X is negative. Question 20 If the correlation coefficient (r) = 1.00, then the Y-intercept (b0) must equal 0. the explained variation equals the unexplained variation. there is no unexplained variation. there is no explained variation. Question 21 TABLE 13-12 The manager of the purchasing department of a large saving and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: Note: 4.3946E-15 is 4.3946 x 10-15 Referring to Table 13-12, the estimated mean amount of time it takes to record one additional loan application is 0.4024 fewer hours. 0.4024 more hours. 0.0126 fewer hours. 0.0126 more hours. Question 22 TABLE 13-12 The manager of the purchasing department of a large saving and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: Note: 4.3946E-15 is 4.3946 x 10-15 Referring to Table 13-12, the p-value of the measured F test statistic to test whether the number of loan applications recorded affects the amount of time is (4.3946E-15)/2. 4.3946E-15. (0.0030)/2. 0.0030. Question 23 TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: Referring to Table 13-2, what is the estimated mean change in the sales of the candy bar if price goes up by $1.00? 161.386 0.784 -3.810 -48.193 Question 24 TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: Referring to Table 13-2, what is the coefficient of correlation for these data? -0.8854 -0.7839 0.7839 0.8854 Question 25 TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: Referring to Table 13-2, what is the percentage of the total variation in candy bar sales explained by the regression model? 100% 88.54% 78.39% 48.19% Question 26 TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: Referring to Table 13-2, if the price of the candy bar is set at $2, the estimated mean sales will be 30. 65. 90. 100. Question 27 TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output for predicting GPA using ACT scores based a data set of 8 randomly chosen students from a Big-Ten university. Referring to Table 13-8, the interpretation of the coefficient of determination in this regression is 57.74% of the total variation of ACT scores can be explained by GPA. ACT scores account for 57.74% of the total fluctuation in GPA. GPA accounts for 57.74% of the variability of ACT scores. None of these. Question 28 TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output for predicting GPA using ACT scores based a data set of 8 randomly chosen students from a Big-Ten university. Referring to Table 13-8, what is the predicted value of GPA when ACT = 20? 2.61 2.66 2.80 3.12 Question 29 TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output for predicting GPA using ACT scores based a data set of 8 randomly chosen students from a Big-Ten university. Referring to Table 13-8, the value of the measured test statistic to test whether there is any linear relationship between GPA and ACT is 0.0356. 0.1021. 0.7598. 2.8633. Question 30 TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output for predicting GPA using ACT scores based a data set of 8 randomly chosen students from a Big-Ten university. Referring to Table 13-8, what are the decision and conclusion on testing whether there is any linear relationship at 1% level of significance between GPA and ACT scores? Do not reject the null hypothesis; hence there is insufficient evidence to show that ACT scores and GPA are linearly related. Reject the null hypothesis; hence there is insufficient evidence to show that ACT scores and GPA are linearly related. Do not reject the null hypothesis; hence there is sufficient evidence to show that ACT scores and GPA are linearly related. Reject the null hypothesis; hence there is sufficient evidence to show that ACT scores and GPA are linearly related.