How to Run Wilcoxon Signed Rank Test in SPSS (Step-by-Step Guide)

The Wilcoxon Signed Rank Test is a widely used non-parametric statistical test in SPSS for comparing two related samples. It is commonly applied when the assumptions of the paired samples t-test, particularly normality, are violated. Students and researchers in psychology, education, nursing, business, and social sciences frequently use this test to analyze pre-test/post-test data, before-and-after measurements, or matched pairs.

What Is the Wilcoxon Signed Rank Test?

The Wilcoxon Signed Rank Test is a non-parametric alternative to the paired samples t-test. It compares the median difference between two related measurements to determine whether there is a statistically significant change.

Unlike parametric tests, the Wilcoxon test does not assume normally distributed data, making it especially useful when:

• Sample sizes are small
• Data is skewed
• Outliers are present
• The normality assumption is violated

When Should You Use the Wilcoxon Signed Rank Test?

You should use the Wilcoxon Signed Rank Test when all of the following conditions are met:

Condition	Requirement
Data type	Continuous or ordinal
Samples	Two related or paired samples
Design	Repeated measures or matched pairs
Normality	Violated or uncertain
Independence	Observations are paired, not independent

Common Research Examples

• Pre-test vs post-test scores
• Stress levels before and after an intervention
• Customer satisfaction before and after service improvement
• Blood pressure before and after treatment

Wilcoxon Signed Rank Test vs Paired Samples t-Test

Feature	Paired t-Test	Wilcoxon Signed Rank Test
Data distribution	Normal	Not required
Test type	Parametric	Non-parametric
Central tendency	Mean	Median
Sensitivity	Higher	More robust
Use case	Ideal conditions	Violated assumptions

If your data is not normally distributed, the Wilcoxon Signed Rank Test is the correct choice.

Step 1: Prepare Your Data in SPSS

Before running the test, your dataset must be structured correctly.

Data Setup Requirements

• Each row represents one participant
• Each column represents one condition or time point
• No missing values within pairs

Example Data Structure

Participant	Pre_Test	Post_Test
1	45	52
2	38	40
3	50	55
4	42	41

Ensure both variables are set to Scale in the Variable View.

Step 2: Check the Normality Assumption (Recommended)

Although the Wilcoxon test does not require normality, it is good academic practice to test normality first to justify using a non-parametric test.

How to Check Normality in SPSS

1. Click Analyze
2. Select Descriptive Statistics
3. Click Explore
4. Move your difference scores or variables into the Dependent List
5. Click Plots
6. Select Normality plots with tests
7. Click OK

If the Shapiro–Wilk test is significant (p < .05), normality is violated, supporting the use of the Wilcoxon Signed Rank Test.

Step 3: Run the Wilcoxon Signed Rank Test in SPSS

SPSS Menu Steps

1. Click Analyze
2. Select Nonparametric Tests
3. Choose Related Samples
4. Select Wilcoxon
5. Move your two related variables into the test fields
6. Click Run or OK

SPSS will generate the output automatically.

Step 4: Understanding the SPSS Output

SPSS provides three key tables for the Wilcoxon Signed Rank Test.

1. Ranks Table

This table shows how many cases increased, decreased, or stayed the same.

Category	Meaning
Positive Ranks	Post-test > Pre-test
Negative Ranks	Post-test < Pre-test
Ties	No change

This table helps you understand the direction of change.

2. Test Statistics Table

This is the most important table for decision-making.

Statistic	Meaning
Z	Standardized test statistic
Asymp. Sig. (2-tailed)	p-value

Decision Rule

• If p < .05 → Statistically significant difference
• If p ≥ .05 → No significant difference

3. Effect Size (Optional but Recommended)

SPSS does not automatically compute effect size for the Wilcoxon test, but it is recommended for dissertations and theses.

Effect Size Formula

$$r = \frac{Z}{\sqrt{N}}$$​

Where:

• Z = Z-value from SPSS output
• N = Total number of observations

Step 5: Interpreting the Results

Interpretation should focus on:

• Direction of change
• Statistical significance
• Practical meaning

Example Interpretation

The Wilcoxon Signed Rank Test showed a statistically significant increase in post-test scores compared to pre-test scores, Z = −2.45, p = .014, indicating that the intervention was effective.

Step 6: How to Report Wilcoxon Signed Rank Test Results in APA Style

Correct APA reporting is essential for academic assignments and dissertations.

APA Example

A Wilcoxon Signed Rank Test indicated a statistically significant difference between pre-test and post-test scores, Z = −2.45, p = .014.

If effect size is included:

The effect size was moderate (r = .43).

Common Mistakes Students Make

1. Using Wilcoxon without justifying non-normality
2. Reporting means instead of medians
3. Forgetting to state whether the test is two-tailed
4. Misinterpreting the Z-value sign
5. Omitting effect size in dissertations

Avoiding these errors improves grades and examiner confidence.

Wilcoxon Signed Rank Test in Assignments and Dissertations

This test is commonly accepted in:

• Undergraduate statistics assignments
• Master’s research projects
• PhD and DBA dissertations (when justified)
• Nursing and healthcare studies
• Education intervention research

Examiners expect clear justification, correct execution, and proper reporting.

When You Should Seek SPSS Help

If you are unsure about:

• Whether Wilcoxon is appropriate
• How to justify non-parametric testing
• How to interpret output
• How to write APA-style results

Professional SPSS support can save time and prevent costly mistakes.

At spssdissertationhelp.com, we assist students with:

• Choosing the correct statistical test
• Running Wilcoxon Signed Rank Test in SPSS
• Interpreting and reporting results correctly
• Fixing rejected or revised analysis

Frequently Asked Questions

Is the Wilcoxon Signed Rank Test parametric?

No. It is a non-parametric test.

Can I use Wilcoxon for more than two groups?

No. It is only for two related samples.

What if my data has ties?

SPSS handles ties automatically.

Should I report medians or means?

You should report medians for non-parametric tests.

Final Thoughts

Understanding how to run Wilcoxon Signed Rank Test in SPSS is essential for analyzing paired data when normality assumptions are violated. When used correctly, this test provides reliable and academically accepted results.

If you need expert help running or interpreting the Wilcoxon Signed Rank Test, professional SPSS assistance can ensure your analysis is accurate, defensible, and properly reported.