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How to Do The Mann-Whitney U Test on GraphPad Prism

  • 1 day ago
  • 5 min read
How to Do The Mann-Whitney U Test on GraphPad Prism

If you are analyzing non-normal data from two independent groups—like comparing protein expression in "Control vs. Treated" mice or patient recovery scores—you need the Mann-Whitney U test.

This guide is your definitive resource for performing, interpreting, and reporting the Mann-Whitney U test using GraphPad Prism. We move beyond basic button-clicking to cover the "Why," the "How," and the critical troubleshooting steps real scientists face in the lab.



What is the Mann-Whitney U Test?

The Mann-Whitney U test (also known as the Wilcoxon rank-sum test) is the non-parametric alternative to the unpaired Student's t-test.

Unlike the t-test, which compares means and assumes your data follows a bell curve (Gaussian distribution), the Mann-Whitney U test compares ranks. It doesn’t care about the specific values, only their order from lowest to highest. This makes it perfect for the skewed, small-sample data often found in pre-clinical research (e.g., Western blot densitometry, cytokine assays).

  • Null Hypothesis (H0): The distributions of both groups are identical (randomly selected values from one group are equally likely to be greater or less than values from the other).

  • Alternative Hypothesis (H1): The distributions are different (values in one group tend to be larger than the other).


Checklist: When to Use This Test

Before you open GraphPad, ensure your experimental design meets these criteria. Violating these assumptions is a common reason for manuscript rejection.

  • Experiment Type: You have two distinct groups (e.g., Wild-type vs. Knockout).

  • Independence: The data is unpaired. (If you measured the same mouse before and after treatment, use the Wilcoxon Matched-Pairs Signed Rank Test instead).

  • Data Type: Your data is continuous (enzyme activity, weight) or ordinal (clinical scores, histology grades).

  • Distribution: Your data is not normally distributed (or your sample size is too small, e.g., n < 6, to prove normality).

  • Shape: To interpret the result specifically as a difference in medians, the distributions of both groups should have roughly the same shape (even if that shape is weird).


Step-by-Step Protocol: Mann-Whitney in GraphPad Prism

1. Data Entry

  1. Open GraphPad Prism.

  2. Select Column from the left-hand menu under "New Table & Graph".

  3. Choose Enter replicate values, stacked into columns.

  4. Click Create.

  5. Label Column A (e.g., "Control") and Column B (e.g., "Drug X").

  6. Paste your raw data into the columns. Do not paste calculated means or SDs.


2. Running the Analysis

  1. Click the Analyze button in the toolbar.

  2. Under Column analyses, select t-tests (and nonparametric tests).

  3. Ensure your two datasets are checked in the right panel. Click OK.


3. Configuring Parameters (Crucial Step)

A dialog box will appear. Configure it exactly as follows for a standard biomedical experiment:

  • Experimental Design: Select Unpaired.

  • Assume Gaussian Distribution: Select No (Use nonparametric test).

  • Choose Test: Select Mann-Whitney test.

  • Options Tab (Recommended):

    • Descriptive Statistics: Check "Report descriptive statistics for each data set." (You need this for the Median and IQR).

    • P-value style: Select "GP" (0.1234) or Scientific depending on your journal's requirements.

Click OK to run the test.


Interpreting Your Results

GraphPad will generate a "Tabular Results" sheet. Here is how to read it like a statistician.


The P-Value

Look at the row labeled P value.

  • P < 0.05: Significant. You reject the null hypothesis. The ranks of the two groups are different.

  • Exact vs. Approximate: For small sample sizes (typically n < 20 per group), GraphPad calculates an Exact P-value. For larger samples, it uses a Gaussian approximation. Always report the Exact P-value if available as it is more robust.


Mann-Whitney U Statistic

This represents the number of times a value from one group precedes a value from the other in the ranked list. While less intuitive than a t-value, it must be reported in your thesis or detailed stats table.


The Median Difference (Hodges-Lehmann)

GraphPad estimates the difference between the two populations.

  • Note: If the difference between medians is 0.0, but the P-value is significant, your distributions might have different shapes (e.g., different spreads) rather than different locations.


How to Report Results in a Manuscript

Do not write "p < 0.05" and move on. Follow this template to satisfy Reviewer #2.

Template:

"Data were analyzed using the non-parametric Mann-Whitney U test as they did not follow a normal distribution (confirmed by Shapiro-Wilk test). Results are presented as median [interquartile range]. The treated group displayed significantly higher protein levels (Median: 12.5 [IQR: 10.1–14.2]) compared to controls (Median: 4.2 [IQR: 2.1–5.5]); U=14, p=0.0021."

Key Rules:

  • Never report Mean ± SEM for a Mann-Whitney test. It is misleading. Always report Median and IQR (or Range).

  • State the U statistic (e.g., U=14).

  • State the n number for each group.




Mann-Whitney in GraphPad Prism Troubleshooting & FAQs

My graph shows a significant difference (p < 0.05), but the error bars overlap heavily. Why?

You might be plotting Mean ± SEM while testing Ranks. Change your graph to a "Box and Whiskers" plot or plot the Median with Interquartile Range to visually match your statistical test.

GraphPad didn't give me a P-value!

This happens in extreme cases, such as "All Zeros" in one group and very few samples in the other (e.g., n=2). The test lacks power to resolve a p-value. You may need to increase your sample size or simply report "undetectable levels in control group."

What if I have "Ties" in my data?

Ties occur when two samples have the exact same value. GraphPad handles this automatically using the "corrected" method. You generally don't need to worry about this unless a massive portion of your data is identical.

Can I use this for 3 groups?

No. Doing multiple Mann-Whitney tests (A vs B, B vs C, A vs C) increases your Type I error rate (false positives). Use the Kruskal-Wallis test instead.

How do I perform a Mann-Whitney U test?

In GraphPad Prism, enter your data into two separate columns (Column table). Click Analyze > t-tests (and nonparametric tests). In the dialogue box, set the Experimental Design to Unpaired and select No (Use nonparametric test). This automatically selects the Mann-Whitney test. Click OK to generate your P-value and U-statistic.

What is the difference between the Mann-Whitney and Kruskal-Wallis test?

The difference lies in the number of groups you are comparing.

  • Mann-Whitney U: Used for comparing two independent groups (e.g., Control vs. Treatment). It is the non-parametric equivalent of the unpaired t-test.

  • Kruskal-Wallis: Used for comparing three or more groups (e.g., Control vs. Low Dose vs. High Dose). It is the non-parametric equivalent of a One-Way ANOVA.

  • Warning: Do not run multiple Mann-Whitney tests to compare three groups (e.g., A vs B, B vs C); this increases false positives. Use Kruskal-Wallis instead.




References


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