BNAL TEST 2 QUIZ QUESTIONS WITH VERIFIED SOLUTIONS LATEST UPDATE 2026

BNAL TEST 2 QUIZ QUESTIONS WITH VERIFIED SOLUTIONS LATEST UPDATE 2026 The y-intercept (B0) represents the a. predicted value of Y when X=0 b. change in estimated Y per unit change in X c. predicted value of Y d. variation around the sample regression line - Answers a. predicted value of Y when X=0 The slope (b1) represents a. the estimated average change in Y per unit change in X b. predicted value of Y when X=0 c. the predicted value of Y d. Variation around the line of regression - Answers a. the estimated average change in Y per unit change in X True of False: The Chancellor of a university has commissioned a team to collect data on students' GPAs and the amount of time they spend bar hopping every week (measured in minutes). He wants to know if imposing much tougher regulations on all campus bars to make it more difficult for students to spend time in any campus bar will have a significant impact on general students' GPAs. His team should use a t test on the slope of the population regression. - Answers True The residual represents the discrepancy between the observed dependent variable and its _______ value. a. the difference between the actual Y values and the mean of Y b. the difference between the actual Y values and the predicted Y values c. the square of the slope d. the predicted value of Y for the average X value - Answers b. the difference between the actual Y values and the predicted Y values The strength of the linear relationship between two numerical variables may be measured by the a. slope b. scatter plot c. coefficient of correlation d. Y-intercept - Answers c. coefficient of correlation In similar linear regression problem, r and b1 a. are equal b. may have opposite signs c. must have opposite signs d. must have the same sign - Answers d. must have the same sign 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? a. 161.386 b. 0.784 c. -3.810 d. -48.193 - Answers -48.193 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? a. 100% b. 88.54% c. 78.39% d. 48.19% - Answers 78.39% 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? a. -0.8854 b. -0.7839 c. 0.7839 d. 0.8854 - Answers -0.8854 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 a. 30 b. 65 c. 90 d. 100 - Answers 65 The following Excel tables are obtained when "Score received on an exam (measured in percentage points)" (Y) is regressed on "percentage attendance" (X) for 22 students in a Statistics for Business and Economics course. Referring to Table 13-6, which of the following statements is true? a. 2% of the total variability in score received can be explained by percentage attendance. b. 14.26% of the total variability in percentage attendance can be explained by score received. c. 14.26% of the total variability in score received can be explained by percentage attendance. d. 2% of the total variability in percentage attendance can be explained by score received. - Answers 2% of the total variability in score received can be explained by percentage attendance. The following Excel tables are obtained when "Score received on an exam (measured in percentage points)" (Y) is regressed on "percentage attendance" (X) for 22 students in a Statistics for Business and Economics course. Referring to Table 13-6, which of the following statements is true? a. If attendance increases by 0.341% , the estimated mean score received will increase by 1 percentage point. b. If attendance increases by 1%, the estimated mean score received will increase by 39.39 percentage points. c. If attendance increases by 1%, the estimated mean score received will increase by 0.341 percentage points. d. If the score received increases by 39.39%, the estimated mean attendance will go up by 1%. - Answers If attendance increases by 1%, the estimated mean score received will increase by 0.341 percentage points. 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? a. For each increase of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. b. For each decrease of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. c. For each decrease of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands d. For each increase - Answers For each increase of 1 thousand downloads, the expected revenue is estimated to increase by $ 3.7297 thousands. 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 coefficient of determination? a. 74.67% of the variation in revenue can be explained by the variation in the number of downloads. b. 75.54% of the variation in revenue can be explained by the variation in the number of downloads. c. 74.67% of the variation in the number of downloads can be explained by the variation in revenue d. 75.54% of the variation in the number of downloads can be explained by the - Answers b. 75.54% of the variation in revenue can be explained by the variation in the number of downloads. 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 null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? a. H0: b1=0 b. H0: b1≠0 c. H0: B1=0 d. H0: B1≠0 - Answers c. H0: B1=0 In a multiple regression problem involving two independent variables, if b1 is computed to be +2.0, it means that a. the relationship between X1 and Y is significant b. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without holding X2 constant c. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without regard to X2 d. the estimated mean of Y is 2 when X1 equals zero - Answers b. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without holding X2 constant A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). The professor randomly selects 6 workers and collects the following information: Referring to Table 14-2, for these data, what is the value for the regression constant, b0? a. 0.616 b. 1.054 c. 6.932 d. 9.103 - Answers c. 6.932 A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). The professor randomly selects 6 workers and collects the following information: Referring to Table 14-2, for these data, what is the estimated coefficient for performance rating, b1? a. 9.103 b. 6.932 c. 1.054 d. 0.616 - Answers c. 1.054 A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). The professor randomly selects 6 workers and collects the following information: Referring to Table 14-2, for these data, what is the estimated coefficient for the number of economics courses taken, b2? a. 9.103 b. 6.932 c. 1.054 d. 0.616 - Answers d. 0.616 A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). The professor randomly selects 6 workers and collects the following information: Referring to Table 14-2, suppose an employee had never taken an economics course and managed to score a 5 on his performance rating. What is his estimated expected wage rate? a. 10.90 b. 12.20 c. 24.87 d. 25.70 - Answers 12.20 A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). The professor randomly selects 6 workers and collects the following information: Referring to Table 14-2, an employee who took 12 economics courses scores 10 on the performance rating. What is her estimated expected wage rate? a. 10.90 b. 12.20 c. 24.87 d. 25.70 - Answers c. 24.87 An economist is interested to see how consumption for an economy (in $ billions) is influenced by gross domestic product ($ billions) and aggregate price (consumer price index). The Microsoft Excel output of this regression is partially reproduced below. SUMMARY OUTPUT Referring to Table 14-3, to test for the significance of the coefficient on aggregate price index, the p-value is a. 0.0001 b. 0.8330 c. 0.8837 d. 0.9999 - Answers 0.8330 An economist is interested to see how consumption for an economy (in $ billions) is influenced by gross domestic product ($ billions) and aggregate price (consumer price index). The Microsoft Excel output of this regression is partially reproduced below.