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In Exercises 14.12-14.21, we repeat the data and provide the sample regression equations for Exercises 4.48 -4.57.

a. Determine the standard error of the estimate.

b. Construct a residual plot.

c. Construct a normal probability plot of the residuals.

y=9-2r

Short Answer

Expert verified

a. The standard error of the estimate is 2.646

b. The residual plot is,

c. The normal probability plot of the residuals is,

Step by step solution

01

Part (a) Step 1: Given Information

Given table:

y^=9-2x

02

Part (a) Step 2: Explanation

MINITAB can be used to calculate the estimate's standard error.
ProcedureforMINITAB:
Step1:SelectStat>Regression>Regressionfromthedrop-downmenu.
Step 2: In the Response column, enter the response (Y)variable.
Step 3: In Predictors, fill in the columns that include the localid="1652192281731" (X)predictor variables.
Step 4: Click the OK button.

MINITAB output:

The standard error of the estimate is2.646based on the MINITAB result.

03

Part (b) Step 3: Given Information

Given table:

y^=9-2x

04

Part (b) Step 4: Explanation

MINITAB is used to create the residual plot.
ProcedureforMINITAB:
Step1:SelectStat>Regression>Regressionfromthedrop-downmenu.
Step 2: In the Response box, type (Y).
Step 3: In Predictors, fill in the (X)columns.
Step 4: In Graphs, under Residuals vs the variables, input the columns xvariables.
Step 5: Click the OK button.

05

Part (c) Step 5: Given Information

Given table:

y^=9-2x

06

Part (c) Step 6: Explanation 

MINITAB is used to create a normal probability plot of residuals.
ProcedureforMINITAB:
Step1:SelectStat>Regression>Regressionfromthedrop-downmenu.
Step 2: In the Response box, type y.
Step 3: In Predictors, fill in the xcolumns.
Step4:SelectNormalprobabilityplotofresidualsfromtheGraphsmenu.
Step 5: Click the OK button.

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Most popular questions from this chapter

In Exercises 14.98-14.108, use the technology of your choice to do the following tasks.
a. Decide whether your can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b) - (h).
b. Determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
c. Find and interpret a 95%Te confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
d. Determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.
e. Find and interpret a 95%prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.
f. Compare and discuss the differences between the confidence interval that you obtained in part (c) and the prediction interval that you obtained in part (e).

14.10 PCBs and Pelicans. The data from Exercise 14.40for shell thickness and concentration of PCBs of 60Anacapa pelican eggs are on the WeissStats site. Specified value of the predictor variable: 220ppm.

Movie Grosses. The data from Exercise14.36 on domestic and overseas grosses for a random sample of 50 movies are on the WeissStats site.

Acreage and Value. The data from Exercise 14.37for lot size (in acres) and assessed value (in thousands of dollars) for a sample of homes in a particular area are on the WeissStats site.

In Exercises 14.70-14.80, use the technology of your choice to do the following tasks.

a. Decide whether you can reasonably apply the regression t-test. If so, then also do part (b).

b. Decide, at the5% significance level, whether the data provide sufficient evidence to conclude that the predictor variable is useful for predicting the response variable.

PCBs and Pelicans.

Use the data points given on the WeissStats site for shell thickness and concentration of PCBs for 60 Anacapa pelican eggs referred to in Exercise 14.40.

In Exercises 14.48, we repeat the information from Exercises 14.12.

a. Decide, at the 10%significance level, whether the data provide sufficient evidence to conclude that xis useful for predicting y:

b. Find a 90%confidence interval for the slope of the population regression line.

x243y357 role="math" localid="1652276835214" y^=2+x

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