A manager wishes to determine the relationship between the number of miles traveled (in hundreds of miles) by her sales representatives and their amount of sales (in thousands ofdollars) per month. Find the equation of the regression line for the given data. What would be the predicted sales if the sales representative traveled 0 miles? Is this reasonable? Whyor why not? Round the predicted sales to the nearest dollar. Round the regression line values to the nearest hundredth.Miles traveled, xD7 8 15 3 1112 3 1031 33 78 62 65 61 48 55 120Sales, yCO A. y = 3.53x + 37.92; $37,920; No; it is not reasonable for a representative to travel 0 miles and have a positive amount of sales.OB. y=3.53x + 37.92; $37,920; Yes; it is reasonable for a representative to travel 0 miles and have a positive amount of sales.OC. y = 3.53x + 37.92; $3792; No; it is not reasonable for a representative to travel 0 miles and have a positive amount of sales.OD. y = 37.92x +3.53; $3792; Yes; it is reasonable for a representative to travel 0 miles and have a positive amount of sales.

The given data is as follows: x y 2 31 3 33 10 78 7 62 8 65 15 61 3 48 1 55 11…

A manager wishes to determine the relationship between the number of miles traveled (in hundreds of miles) by her sales representatives and their amount of sales (in thousands of dollars) per month. Find the equation of the regression line for the given data. What would be the predicted sales if the sales representative traveled 0 miles? Is this reasonable? Why or why not? Round the predicted sales to the nearest dollar. Round the regression line values to the nearest hundredth. Miles traveled, x 2 3 10 7 8 15 3 1 11 Sales, y 31 33 78 62 65 61 48 55 120 G…... OA. ŷ=3.53x + 37.92; $37,920; No; it is not reasonable for a representative to travel 0 miles and have a positive amount of sales. OB. y=3.53x + 37.92; $37,920; Yes; it is reasonable for a representative to travel 0 miles and have a positive amount of sales. OC. y=3.53x + 37.92; $3792; No; it is not reasonable for a representative to travel 0 miles and have a positive amount of sales. OD. = 37.92x+3.53; $3792; Yes; it is reasonable for a representative to travel 0 miles and have a positive amount of sales.

A manager wishes to determine the relationship between the number of miles traveled (in hundreds of miles) by her sales representatives and their amount of sales (in thousands of dollars) per month. Find the equation of the regression line for the given data. What would be the predicted sales if the sales representative traveled 0 miles? Is this reasonable? Why or why not? Round the predicted sales to the nearest dollar. Round the regression line values to the nearest hundredth. Miles traveled, x 2 3 10 7 8 15 3 1 11 Sales, y 31 33 78 62 65 61 48 55 120 G…... OA. ŷ=3.53x + 37.92; $37,920; No; it is not reasonable for a representative to travel 0 miles and have a positive amount of sales. OB. y=3.53x + 37.92; $37,920; Yes; it is reasonable for a representative to travel 0 miles and have a positive amount of sales. OC. y=3.53x + 37.92; $3792; No; it is not reasonable for a representative to travel 0 miles and have a positive amount of sales. OD. = 37.92x+3.53; $3792; Yes; it is reasonable for a representative to travel 0 miles and have a positive amount of sales.

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.CR: Chapter Review Exercises

Problem 15CR: Life Expectancy The following table shows the average life expectancy, in years, of a child born in...

See similar textbooks

Similar questions

Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300
Demand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00
3.4 SKILL BUILDING EXERCISES Getting Regression Lines Only Find the equation of the regression line for the following data set. x 1 2 3 y 3 3 4
For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.