Student Center |

## The One-Way ANOVA with SPSSThe table below shows fictional data for a study of college GPA and class membership. Class refers to whether the individual reports being a first-year, sophomore, junior, or senior student. The analysis would begin by entering the data into the SPSS-Win spreadsheet as described previously. The variables can then be named and labeled as appropriate.
Once the data have been entered, click > One-way ANOVA.... A window will
appear with a list of variables on the left and boxes labeled "Dependent
List" and "Factor" on the right. Transfer the dependent
variable (the variable for which means are to be computed) into the "Dependent
List" box and the independent variable (the variable used as the grouping
variable) into the "Factor" box. Next, click Define Range...
and enter the minimum and maximum for the grouping variable. This may seem like
an unnecessary step but it allows the researcher to exclude extreme values of
the grouping variable. This could be desirable because too few participants
were in one of the categories or a category had a label such as "Does Not
Apply" or "Don't Know"
in which the researcher was not interested. Once the range has been defined,
click Continue. I also recommend clicking the Options... button
and requesting descriptive statistics and a test for homogeneity of variance
by clicking on the appropriate boxes. It may be interesting to take a look at
what is available under the Contrasts... and Post Hoc... buttons which allow
the researcher to select subsequent tests which may be needed to ascertain exactly
where differences between and among the means may be found. Clicking Cancel
takes one back to the main window without any subsequent tests being requested.
Finally, click OK to cause the analysis to be computed.Results are shown below. It begins with descriptive statistics and the results
of the test for homogeneity of variance, ending with the familiar ANOVA summary
table. The key information is the F-ratio and associated probability (F Prob.).
In this example, the difference in GPAs among the four classes was not statistically
significant as shown by the probability which is considerably more than .05.
The Levene test tests the assumption that the group variances are homogenous.
When the results of this test are significant, that is, the "2-tail Sig."
is less than .05, the assumption has been violated. Procedures for dealing with
this situation are discussed in most advanced statistics books. The solution
involves adjusting the degrees of freedom for finding the critical value of
[This nonsignificant result is good because it shows that the homogeneity of variance assumption was not violated. A "Sig." value below .05 would be a cause for concern.]
COLGPA
[The value for "Sig." is greater than .05, therefore the result is NOT significant.] |

Copyright ©2001 The McGraw-Hill Companies.

Any use is subject to the Terms of Use and Privacy Policy.

McGraw-Hill Higher Education is one of the many fine businesses of the The McGraw-Hill Companies.