# Inference for Multiple Linear Regression in MINITABTM

## Chapter 9, Printout 2

1. Launch MINITAB.

2. Enter the data.

• Name Column C1 by clicking the column header below the label "C1" and typing, "x1." Then enter the Air Flow data from the "x1i" column in Table 4.8 (p. 150).

• Name Column C2 "x2" and enter the Cooling Water Inlet Temperature data from the "x2i" column in the table.

• Name Column C3 "x1^2"

• Select "Calc --> Calculator."

• Fill out the resulting dialog box as follows:

Input Type Label Value
Store result in variable: 'x1^2'
Expression: 'x1'**2

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• CLick "OK."

• Name Column C4 "y" and enter the Stack Loss data from the "yi" column in Table 4.8.

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3. Compute the multiple linear regression.

• Select "Stat --> Regression --> Regression."

• Fill out the resulting dialog box as follows:

Input Type Label Value
Response: y
Predictors: x1 x2 'x1^2'

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• Before closing the dialog box, click "Results."

• In the dialog box that follows, click the radio button next to the label, "In addition, the full table of fits and residuals."

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• Click "OK" to close the "Results" dialog box.

• Click "Options."

• Fill out the resulting dialog box as follows:

Input Type Label Value
Weights
Fit intercept checked
Variance inflation factors unchecked
Pure error unchecked
Durbin-Watson statistic unchecked
Data subsetting unchecked
PRESS and predicted R-square unchecked
Prediction intervals for new observations: 60 20 3600
Confidence level: 95
Fits unchecked
Confidence limits unchecked
SE of fits unchecked
Prediction limits unchecked

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• Click "OK" to close the "Options" dialog box.

• Click "OK" in the "Regression" dialog box.

MINITAB displays summary information, including the regression equation, a table of fits and residuals, and a predicted value for x1 = 60, x2 = 20.

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