2024年3月10日发(作者：)

商务与经济统计习题答案（第8版，中文版）SBE8

Chapter 14 Simple Linear Regression Learning Objectives 1. Understand how

regression analysis can be used to develop an equation that estimates

mathematically how two variables are related. 2. Understand the differences

between the regression model, the regression equation, and the estimated

regression equation. 3. Know how to fit an estimated regression equation to a set

of sample data based upon the least-squares method. 4. Be able to determine how

good a fit is provided by the estimated regression equation and compute the

sample correlation coefficient from the regression analysis output. 5. Understand

the assumptions necessary for statistical inference and be able to test for a

significant relationship. 6. Learn how to use a residual plot to make a judgement

as to the validity of the regression assumptions, recognize outliers, and identify

influential observations. 7. Know how to develop confidence interval estimates of

y given a specific value of x in both the case of a mean value of y and an individual

value of y. 8. Be able to compute the sample correlation coefficient from the

regression analysis output. 9. Know the definition of the following terms:

independent and dependent variable simple linear regression regression model

regression equation and estimated regression equation scatter diagram coefficient

of determination standard error of the estimate confidence interval prediction

interval residual plot standardized residual plot outlier influential observation

leverage Solutions: 1 a. b. There appears to be a linear relationship between x and

y. c. Many different straight lines can be drawn to provide a linear approximation

of the relationship between x and y; in part d we will determine the equation of a

straight line that “best” represents the relationship according to the least squares

criterion. d. Summations needed to compute the slope and y-intercept are: e. 2. a.

b. There appears to be a linear relationship between x and y. c. Many different

straight lines can be drawn to provide a linear approximation of the relationship

between x and y; in part d we will determine the equation of a straight line that

“best” represents the relationship according to the least squares criterion. d.

Summations needed to compute the slope and y-intercept are: e. 3. a. b.

Summations needed to compute the slope and y-intercept are: c. 4. a. b. There

appears to be a linear relationship between x and y. c. Many different straight lines

can be drawn to provide a linear approximation of the relationship between x and

y; in part d we will determine the equation of a straight line that “best” represents

the relationship according to the least squares criterion. d. Summations needed to

compute the slope and y-intercept are: e. pounds 5. a. b. There appears to be a

linear relationship between x and y. c. Many different straight lines can be drawn

to provide a linear approximation of the relationship between x and y; in part d we

will determine the equation of a straight line that “best” represents the

relationship according to the least squares criterion. Summations needed to

compute the slope and y-intercept are: d. A one million dollar increase in media

expenditures will increase case sales by approximately 14.42 million. e. 6. a. b. There

appears to be a linear relationship between x and y. c. Summations needed to

compute the slope and y-intercept are: d. A one percent increase in the percentage

of flights arriving on time will decrease the number of complaints per 100,000

passengers by 0.07. e 7. a. b. Let x = DJIA and y = SP. Summations needed to

compute the slope and y-intercept are: c. or approximately 1500 8. a. Summations

needed to compute the slope and y-intercept are: b. Increasing the number of

times an ad is aired by one will increase the number of household exposures by