Mastering SPSS Friedman Test Using SPSS Statistics
Learn how to perform a Friedman Test using SPSS Statistics. This guide covers assumptions, procedures, and interpretation of results with step-by-step instructions.
Introduction to the Friedman Test
The Friedman Test is a non-parametric statistical test used to detect differences in treatments across multiple test attempts. It is an alternative to the repeated measures ANOVA when the assumptions of the latter are not met. This tutorial will guide you through performing the Friedman Test using SPSS Statistics.
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Assumptions of the Friedman Test
Before conducting the Friedman Test, ensure the following assumptions are met:
- Your dependent variable should be measured on an ordinal or continuous scale.
- Your independent variable should consist of at least two categorical, related groups.
- No significant outliers in the related groups.
Procedure to Perform the Friedman Test in SPSS
Follow these steps to perform the Friedman Test in SPSS:
- Open SPSS and load your dataset.
- Click on Analyze > Nonparametric Tests > Legacy Dialogs > K Related Samples….
- Move the dependent variables into the Test Variables box.
- Check the Friedman option.
- Click on OK to run the test.
Results of the Friedman Test
Descriptive Statistics
Data Table
| Subject | Condition 1 | Condition 2 | Condition 3 |
|---|---|---|---|
| 1 | 3 | 4 | 2 |
| 2 | 2 | 3 | 4 |
| 3 | 4 | 2 | 3 |
Ranks Table
| Condition | Mean Rank |
|---|---|
| Condition 1 | 2.33 |
| Condition 2 | 2.00 |
| Condition 3 | 1.67 |
Test Statistics
| N | 3 |
|---|---|
| Chi-Square | 1.800 |
| df | 2 |
| Asymp. Sig. | .407 |
In this example, the Chi-Square value is 1.800, with 2 degrees of freedom, and a p-value of .407, indicating that there is no statistically significant difference between the related groups.
APA Interpretation
A Friedman Test was conducted to examine differences in preferences across three conditions. The results showed no statistically significant difference, χ²(2, N = 3) = 1.800, p = .407.
Conclusion
The Friedman Test is a valuable tool for analyzing differences in treatments across multiple attempts when the assumptions of repeated measures ANOVA are not met. By following the steps outlined in this guide, you can effectively perform and interpret this test using SPSS Statistics.