One way anova in spss (procedure and output)

The presentation contains the stepwise procedure to conduct One way ANOVA (Analysis of Variance) using IBM SPSS.

1. One way ANOVA
(Procedure and Output in SPSS)

2. Data View
Data view represents the
cases/data points for
different variables.

3. Variable View
Variable view represents the
properties of all variables.
One can toggle between
data and variable view with
the shortcut ctrl + t.

4. Step 1
Running One way ANOVA:
Go to the Analyze tab in
Menu bar, click on Compare
Means option and select
One way ANOVA

5. Step 2
Selecting Variable:
Select continuous variable
and click on arrow to drag it
in Dependent list then drag
categorical variable in the
factor list

6. Step 3
Selecting Variable:
Selected variables are
represented in Dependent
list and Factor box.

7. Step 4
Selecting Post hoc Test:
Click on the Post hoc button
to select appropriate post
hoc test.

8. Step 5
Choosing Post hoc
Test:
Select Tukey if
variables have equal
variance, if
homogeneity of
variance assumption
is violated then select
Games-howellor
Dunnet’s C from the
Equal variance no
assumed box

9. Step 6
Selecting Statistics Options:
Click on the Option button to
select appropriate test.

10. Step 7
Selecting Statistics:
Select Descriptive to see
descriptive statistics, and
Homogeneity of variance
to check assumption for
equal variance. If this
assumption violated the
select Brown-Forsythe and
Welch for robust test.

11. Step 8
Running Analysis:
Click on the OK button to
get the output window
with results.

12. Output
This first table displays the
descriptive statistics for
sub-groups and overall.

13. Homogeneity of Variance Output
Levene Statistic for
equality of variance
Degree of freedom
(between groups)
Degree of freedom
(within groups)
Significance value
associated with Levene
statistic

14. ANOVA table
F –statistic to test
hypothesis for equality
of mean in groups with
it’s associated
significance value
Sum of squares with degree
of freedom and mean
squares for between groups
and within groups.

15. Post hoc (Multiple Comparison Table)
This table displays comparison of
mean differences with it’s associated
significance value. It also displays 95%
Confidence interval for Mean
difference

16. Homogeneous Subsets
This table displays the homogeneous
subset for the sample.

17. Developed and designed by:
Address: Mau -Chitrakoot
Contact: [email protected]