3. The Quick Sell car dealership has been using 1-minute spot ads on a local TV station. The ads are always run during the evening hours and advertise the different models and price ranges of cars on the lot that week. During a 5-week period, the Quick Sell dealer kept a weekly record of the number of TV ads versus the number of cars sold. The results are shown below. Let x represent the number of ads in a week and let y represent the number of cars sold that week. 8 1. 15 a. Make a scatterplot for the data. b. 15 16 Ads per week (x) Cars sold per week (y) Suppose x = 13, s, 9.1, y = 18.8, s, = 8.7, and r = .91. 20 30 0 8 22 25 Based on your answer to part a., describe the association between the two variables. Explain. c. Find the equation of the least squares regression line (round a and b to the nearest tenth). d. What is the slope of the regression line? Explain its meaning relative to this problem situation. e. List 2 points that you know will be on the least-squares line you found in part c. f. Graph the least-squares line on your scatterplot from part a. g. What percent of variation is accounted for by a linear relationship? h. Use the equation of the least-squares regression line to predict the number of cars sold per week when 5 ads are run during the week. Would it make sense to use the least-squares line to predict the number of cars sold per week when 40 ads are run during the week? Explain using any appropriate terms.
3. The Quick Sell car dealership has been using 1-minute spot ads on a local TV station. The ads are always run during the evening hours and advertise the different models and price ranges of cars on the lot that week. During a 5-week period, the Quick Sell dealer kept a weekly record of the number of TV ads versus the number of cars sold. The results are shown below. Let x represent the number of ads in a week and let y represent the number of cars sold that week. 8 1. 15 a. Make a scatterplot for the data. b. 15 16 Ads per week (x) Cars sold per week (y) Suppose x = 13, s, 9.1, y = 18.8, s, = 8.7, and r = .91. 20 30 0 8 22 25 Based on your answer to part a., describe the association between the two variables. Explain. c. Find the equation of the least squares regression line (round a and b to the nearest tenth). d. What is the slope of the regression line? Explain its meaning relative to this problem situation. e. List 2 points that you know will be on the least-squares line you found in part c. f. Graph the least-squares line on your scatterplot from part a. g. What percent of variation is accounted for by a linear relationship? h. Use the equation of the least-squares regression line to predict the number of cars sold per week when 5 ads are run during the week. Would it make sense to use the least-squares line to predict the number of cars sold per week when 40 ads are run during the week? Explain using any appropriate terms.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:3. The Quick Sell car dealership has been using 1-minute spot ads on a local TV station. The ads
are always run during the evening hours and advertise the different models and price ranges of
cars on the lot that week. During a 5-week period, the Quick Sell dealer kept a weekly record
of the number of TV ads versus the number of cars sold. The results are shown below. Let x
represent the number of ads in a week and let y represent the number of cars sold that week.
8
1.
20
15
16
30
Ads per week (x)
Cars sold per week (y)
Suppose x = 13, s, = 9.1, y = 18.8, s, = 8.7, and r = .91.
15
0
8
22
25
a. Make a scatterplot for the data.
b. Based on your answer to part a., describe the association between the two variables.
Explain.
c. Find the equation of the least squares regression line (round a and b to the nearest
tenth).
d. What is the slope of the regression line? Explain its meaning relative to this problem
situation.
e. List 2 points that you know will be on the least-squares line you found in part c.
f. Graph the least-squares line on your scatterplot from part a.
g. What percent of variation is accounted for by a linear relationship?
h. Use the equation of the least-squares regression line to predict the number of cars sold
per week when 5 ads are run during the week.
Would it make sense to use the least-squares line to predict the number of cars sold per
week when 40 ads are run during the week? Explain using any appropriate terms.
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