Chapter 6
Regression
This tutorial describes the procedures for making a scatter plot and computing regression
coefficients. The midterm and final exam grades in Table 6.2-1 of the textbook are used to
illustrate the procedures.
1. Enter the data into the SPSS Data Editor following steps 1–7 described in the Frequency
Distribution Program for Chapter 2. The SPSS Data Editor Variable View and Data View
windows should be similar to the windows shown here.
2. The linear regression procedure assumes that the two variables are linearly related. The
tenability of the assumption can be checked by examining a scatterplot of the variables. To
obtain the scatterplot, click on Graphs in the Menu Bar. Select Legacy Dialogs from the
© 2008 Roger E. Kirk
Regression
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pull-down menu and then Scatter/Dot. This selection opens the Scatter/Dot window
shown here.
3. Select Simple Scatter in the upper left corner of the Scatter/Dot window and then click on
the Define button. This action opens the Simple Scatterplot window shown here where you
identify the variables on the horizontal, X, axis and the vertical, Y, axis.
© 2008 Roger E. Kirk
Regression
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4. Select Midterm grade (Mid_grade) in the box on the left and click on the arrow button
beside the X Axis box on the right to move Midterm grade (Mid_grade) into the X Axis
box. Select Final exam grade (Fin_grade) in the box on the left and click on the arrow
button beside the Y Axis box to move Final exam grade (Fin_grade) into the Y Axis box.
Click on the highlighted OK button in the lower right corner of the Simple Scatterplot
window to obtain the scatterplot shown here. An examination of the scatterplot suggests that
there is no reason to question the assumption that the variables are linearly related.
5. To obtain the coefficients for the linear regression equation, click on Analyze in the Menu
Bar, select Regression from the pull-down menu and then Linear. These selections open
the Linear Regression window shown here.
© 2008 Roger E. Kirk
Regression
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6. Select Midterm grade (Mid_grade) in the box on the left and click on the arrow button
beside the Independent(s) box on the right to move Midterm grade (Mid_grade) into the
Independent(s) variable box. Select Final exam grade (Fin_grade) in the box on the
left and click on the arrow button beside the Dependent(s) variable box to move Final
exam grade (Fin_grade) into the Dependent variable box. Then click on the Statistics
button in the upper right part of the Linear Regression window. This opens the Linear
Regression: Statistics window shown here.
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Regression
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7. Check the Estimates box in the upper left corner of the Linear Regression: Statistics
window and then the Model fit box in the upper right corner of the window. Then click the
Continue button to return to the Linear Regression window.
8. The OK button in the lower right part of the Linear Regression window is available. Click
on the OK button to obtain the output of the regression program shown here.
© 2008 Roger E. Kirk
Regression
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QuickTime™ and a
decompressor
are needed to see this picture.
9. The equation for predicting a Final exam grade, Y, from a Midterm grade, X, is
Y = 12.189 + 0.803X.
The Midterm grade accounts for R2 = 64.7% of the variance in the Final exam grade.
© 2008 Roger E. Kirk