Solution:
B) 3.103
Explanation:
Multiple regression using matrix method,
Thus, you can see b1=3.1034
manager of a product sales group believes the number of sales made by an employee (Y)...
QUESTION 9 SCENARIO 14-1 A manager of a product sales group believes the number of sales made by an employee ( depends on how many years that employee has been with the company (X 1) and how he/she scored on a business aptitude test (X2). A random sample of 8 employees provides the following Employee Y 100 90 80 70 60 50 40 30 10 4 4 Referring to Scenario 14-1, for these data, what is the estimated coefficient for...
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: X1 X2 Employee 1. Y ($) 10 _30 2 - 12 اس ادامه 4 15 17 20 Coo- 7 25 10 Referring to Table 14-2, suppose an employee had never taken an economics course and...
(a) A company would like to predict how its trainees in sales will perform based on the results of aptitude test that is given to them at the beginning of the training. The table below contains the test scores (x values) and the values of the sales for these trainees during the first month of working at the company (y values in hundreds of dollars). Salesman 1 2 3 4 5 6 7 8 9 1.8 2.6 2.8 3.4 3.6...
Question 8 (1 point) Given that y = } (x1 + x2)c, what is y when x1 = 3, x2 = 5, and c = 6? Do not include y= in your answer. . BI U Format Question 7 (1 point) Find the equation of the line through (8,-6) which is perpendicular to the line y = -7. Give your answer in the form y = mx + b Format B I U Question 4 (1 point) Which of the...
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is y = 82 + 4x. Salesperson Years of Experience Annual Sales ($1,000s) 80 97 102 107 103 101 119 o 128 11 127 10 13 136 (a) Compute the residuals. (a) Compute the residuals. Years of Experience Annual Sales ($1,000s) Residuals 102 107 103 101 119 128 127 136 Construct a residual plot....
The general manager of a chain of furniture stores believes that experience is the most important factor in determining the level of success of a salesperson. To examine this belief she records last month’s sales (in $1,000s) and the years of experience of 10 randomly selected salespeople. These data are listed below. Salesperson Years of Experience Sales ($1,000s) 1 0 7 2 2 9 3 10 20 4 3 15 5 8 18 6 5 14 7 12 20 8...
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is ŷ = 80 + 4x. Salesperson Years of Experience Annual Sales ($1,000s) 1 1 80 2 3 97 3 4 97 4 4 102 5 6 103 6 8 101 7 10 119 8 10 118 9 11 127 10 13 136 (a) Compute SST, SSR, and SSE. SST= SSR= SSE= (b) Compute...
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is ý = 81 + 4x. Salesperson Years of Experience Annual Sales ($1,000s) 1 107 103 101 119 8 9 10 10 11 13 123 127 136 (a) Compute SST, SSR, and SSE. SST = SSR = SSE = (b) Compute the coefficient of determination 2. (Round your answer to three decimal places.) 12...
1 Problem 7 (20 marks) A sales manager for an advertising agency believes there is a relationship between the number of contacts and the amount of the sales. To verify this believe, the following data was collected: Salesperson Number of Contacts Sales (in thousands) 14 24 2 12 14 3 20 28 4 16 30 16 80 23 7 48 90 50 85 55 120 10 SO 110 6 8 9 Assume normality of variables. a) Calculate the coefficient of...
1 Problem 8 (20 marks) A sales manager for an advertising agency believes there is a relationship between the number of contacts and the amount of the sales. To verify this belief, the following data was collected: Salesperson Number of Contacts Sales (in thousands) 14 24 2 12 14 3 20 28 4 16 30 5 46 80 6 23 30 7 48 90 8 50 85 55 120 10 50 110 9 Assume normality of variables. a) Calculate the...