SPSS calculates an F-statistic (ANOVA) or an H-statistic (Kruskal-Wallis) with exact probability. In other words, you do not need to check a table to determine if a finding is significant.
Determine whether the data in the exercises meet the stringent assumptions of the comparison of means. For ANOVA, determine that the dependent variable has interval data and that the independent variable is nominal. Also, determine whether the data meet the assumption of homogeneity of variance. Check Brown's discussion carefully. Finally, you will need to determine whether the dependent data for each group are normally distributed.
Because the dependent data in the data files are not listed by groups, learn the following procedures to calculate descriptive statistics for each group.
Performing ANOVA
First create or open a data file in SPSS. Do the necessary descriptive statistics. To
access individual groups
in the dependent data, select that group of data using the independent variable.
The following procedure selects the part of the dependent data that
matches the equation. Verify this selection
by moving through the data file itself.
- Click "Select Cases" in the "Data" menu to open the window
- Click "If condition is satisfied"
- Click on "Independent Variable"
- Select the relevant equation (e.g., "=0")
- Click "Ok"
- Click "Ok" (again)
Next, perform descriptive statistics on the selected data from the dependent variable. Repeat the procedure above to select other data on the dependent variable. Repeat descriptive statistics on this data. Repeat these steps for all of the individual groups defined by the independent variable.
When you finish, click "Select Cases" and click "All Data."
One-way ANOVA
To perform one-way ANOVA
Two-way ANOVA
- Select "Analyze" then "Compare Means" then "One-Way ANOVA"
- Click on "Dependent Variable"
- Click on "Independent Variable"
- Click on "Post-Hoc" then "Scheffe" for more than two levels on the independent variable
- Click "Ok"
The result of calculating a one-way ANOVA (three levels) and a Scheffe test is shown below:
- Select "Statistics" then "Analyze" then "General Linear Model" then "Univariate"
- Click on "Dependent Variable"
- Select each independent variable
- Click "Ok"
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Variable TWO
By Variable ONEAnalysis of Variance
Sum of Mean F F
Source D.F. Squares Squares Ratio Prob.Between Groups 2 686960.1067 343480.0533 4.7115 .0119
Within Groups 72 5249007.280 72902.8789
Total 74 5935967.387
This is the ANOVA table; F-ratio and P are on the right.
Standard Standard
Group Count Mean Deviation Error 95 Pct Conf Int for MeanGrp 0 25 1447.4800 264.2297 52.8459 1338.4113 TO 1556.5487
Grp 1 25 1273.8000 262.6573 52.5315 1165.3804 TO 1382.2196
Grp 2 25 1224.2800 282.6702 56.5340 1107.5995 TO 1340.9605Total 75 1315.1867 283.2239 32.7039 1250.0228 TO 1380.3506
GROUP MINIMUM MAXIMUM
Grp 0 986.0000 2071.0000
Grp 1 885.0000 1906.0000
Grp 2 715.0000 1926.0000TOTAL 715.0000 2071.0000
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Variable TWO
By Variable ONEMultiple Range Tests: Scheffe test with significance level .05
The difference between two means is significant if
MEAN(J)-MEAN(I) >= 190.9226 * RANGE * SQRT(1/N(I) + 1/N(J))
with the following value(s) for RANGE: 3.53(*) Indicates significant differences which are shown in the lower triangle
G G G
r r r
p p p2 1 0
Mean ONE1224.2800 Grp 2
1273.8000 Grp 1
1447.4800 Grp 0 *
The information above is from Scheffe. This one shows a significant difference only between groups "0" and "2".
Homogeneous Subsets (highest and lowest means are not significantly different)
Subset 1
Group Grp 2 Grp 1
Mean 1224.2800 1273.8000
- - - - - - - - - - - - - - - - -Subset 2
Group Grp 1 Grp 0
Mean 1273.8000 1447.4800
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