Two way anova in spss (procedure and output)

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

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

2. Step 1
Running Two way ANOVA:
Go to the Analyze tab in
Menu bar, click on
Generalized Linear Model
option and select Univariate
to run Two way ANOVA

3. Step 2
Selecting Variable:
Select continuous variable
and click on arrow to drag
it in Dependent Variable
box then drag categorical
variable in the Fixed or
random factor box
according to model.

4. Step 3
Selecting profile plots:
Click on the Plots button
that will open Univariate:
Profile plot dialog box.

5. Step 4
Selecting Factors:
Drag factors between
which one want to display
Means plot to Horizontal
axis and Separate line
boxes.

6. Step 5
Selecting Factors:
Click on Add button to add
factor combination for
means plot to Plots box

7. Step 6
Selecting Post hoc Test:
Click on the Post hoc
button to select
appropriate post hoc test.

8. Step 7
Selecting Post hoc Test:
Select the factors for
which you want to run
post hoc test and drag it
to “Post hoc test for”
box, then select Tukey
from Equal variance
assumed box.

9. Step 8
Selecting Statistics
Options:
Click on the Option
button to select
appropriate test.

10. Step 9
Selecting Statistics
Options:
Select factors for which
you want to display means
and in the below box
select descriptive statistics
and Homogeneity Test.

11. Step 10
Click on OK button to get
the Output window with
result

12. Factors’ Description
This table displays the
different sub group of
factors with their sample
size

13. Descriptive Statistics
This table displays the
basic descriptive statistics
for each factor group.

14. Homogeneity Test
This table displays the F statistic
associated with significance
value to test the null hypothesis
that the error variance of the
dependent variable is equal
across groups.

15. ANOVA Test
This table displays the result to test null
hypothesis of Two way ANOVA that the variable
will have no significant effect on Dependent
Variable. We can check this by looking at F –
statistic and it’s associated significance value

16. Estimated Marginal Mean
This table displays the
Estimated mean and
Standard Error for the
factors that we chose in
Step 9

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

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

19. Means Plot
This Graph displays the
Means plot for the Variables
that we chosen in Step 4 and
5.

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