Chapter 12 Minitab Instructions
Constructing a Scatterplot with Trendline
A. (Replicating 12.2) Copy and paste the data labeled Debt_Payments from the text website into
a Minitab spreadsheet.
B. From the menu choose Graph > Scatterplot > With Regression. Select Debt as Y variables
and select Income as X variables. Click OK.
C. Minitab shows the following graph. Double-click on title and/or axes titles to make any
necessary edits.
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Scatterplot with a superimposed trend line
1300
Debt payments ($)
1200
1100
1000
900
800
700
60
70
80
90
Income ($1,000s)
100
110
Simple Linear Regression
A. (Replicating Example 12.2) Copy and paste the data labeled Debt_Payments from the text
website into a Minitab spreadsheet.
B. From the menu choose Stat > Regression > Regression. Select Debt as Response and select
Income as Predictors. Click OK.
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C. Minitab reports the following output.
Regression Analysis: Debt versus Income
The regression equation is
Debt = 210 + 10.4 Income
Predictor
Constant
Income
Coef
210.30
10.441
S = 63.2606
SE Coef
91.34
1.222
R-Sq = 75.3%
T
2.30
8.54
P
0.030
0.000
R-Sq(adj) = 74.2%
Analysis of Variance
Source
Regression
Residual Error
Total
DF
1
24
25
SS
292137
96046
388182
MS
292137
4002
F
73.00
P
0.000
Unusual Observations
Obs
1
Income
104
Debt
1285.0
Fit
1291.0
SE Fit
38.1
Residual
-6.0
St Resid
-0.12 X
X denotes an observation whose X value gives it large leverage.
3
Multiple Regression
A. (Replicating Example 12.3) Copy and paste the data labeled Debt_Payments from the text
website into a Minitab spreadsheet.
B. From the menu choose Stat > Regression > Regression. Select Debt as Response and select
Income and Unemployment as Predictors. Click OK.
C. Minitab reports the following output.
Regression Analysis: Debt versus Income, Unemployment
The regression equation is
Debt = 199 + 10.5 Income + 0.62 Unemployment
Predictor
Constant
Income
Unemployment
Coef
199.0
10.512
0.619
SE Coef
156.4
1.477
6.868
S = 64.6098
R-Sq = 75.3%
T
1.27
7.12
0.09
P
0.216
0.000
0.929
R-Sq(adj) = 73.1%
Analysis of Variance
Source
Regression
Residual Error
Total
Source
DF
2
23
25
DF
SS
292171
96012
388182
MS
146085
4174
F
35.00
P
0.000
Seq SS
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Income
Unemployment
1
1
292137
34
Unusual Observations
Obs
1
23
Income
104
70
Debt
1285.0
832.0
Fit
1290.9
942.5
SE Fit
38.9
39.8
Residual
-5.9
-110.5
St Resid
-0.11 X
-2.17RX
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
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