Wilcoxon Signed-Rank Calculator

Run a paired nonparametric Wilcoxon signed-rank test from paired samples or differences

Example Results

1 examples

Test paired before-after changes

Use Wilcoxon signed-rank when paired differences are not assumed normal

{
  "result": {
    "wStatistic": 0,
    "positiveRankSum": 28,
    "negativeRankSum": 0,
    "zStatistic": -2.3456,
    "pValue": 0.019,
    "rejectNull": true
  }
}
View input parameters
{ "inputMode": "paired-samples", "beforeValues": "72, 75, 78, 74, 76, 73, 77", "afterValues": "76, 79, 80, 77, 81, 76, 82", "differenceValues": "4, 4, 2, 3, 5, 3, 5", "alternative": "two-sided", "alpha": 0.05, "decimalPlaces": 4 }

Key Facts

Category
Math, Date & Finance
Input Types
select, textarea, number
Output Type
json
Sample Coverage
4
API Ready
Yes

Overview

The Wilcoxon Signed-Rank Calculator is a nonparametric statistical tool used to compare two related samples or repeated measurements on a single sample. It serves as a robust alternative to the paired t-test when data does not follow a normal distribution, analyzing the ranks of the differences between paired observations to determine statistical significance.

When to Use

  • When comparing paired data that does not meet the normality assumption required for a parametric t-test.
  • When analyzing ordinal data or continuous data containing significant outliers that might skew mean-based results.
  • When evaluating the effectiveness of an intervention by comparing 'before' and 'after' measurements from the same subjects.

How It Works

  • Calculate the difference between each pair of observations or input pre-calculated differences directly into the tool.
  • Rank the absolute values of these differences from smallest to largest, excluding any pairs where the difference is zero.
  • Assign the original signs (positive or negative) to the ranks and calculate the sum of the positive and negative ranks to find the W-statistic.
  • Compute the p-value based on the rank sums and compare it against your chosen alpha level to decide whether to reject the null hypothesis.

Use Cases

Medical researchers comparing patient heart rates before and after administering a specific treatment.
UX designers evaluating task completion times for the same group of users across two different interface versions.
Environmental scientists measuring pollutant levels at the same locations during two different seasons.

Examples

1. Clinical Trial Efficacy Analysis

Medical Researcher
Background
A researcher is testing a new medication intended to reduce blood pressure in a group of 10 patients.
Problem
The collected data is skewed and does not follow a normal distribution, making a standard paired t-test unreliable.
How to Use
Select 'Paired Samples' mode, enter the pre-treatment blood pressure readings in 'Before Values', and the post-treatment readings in 'After Values'.
Example Config
inputMode: 'paired-samples', alpha: 0.05, alternative: 'two-sided'
Outcome
The tool calculates the W-statistic and a p-value of 0.019, indicating a statistically significant change in blood pressure.

2. Software Optimization Testing

QA Engineer
Background
An engineer measures application response times before and after a backend database optimization.
Problem
The differences in response times contain outliers due to network latency, violating normality assumptions.
How to Use
Switch the input mode to 'Differences' and paste the calculated time differences (After minus Before) into the text area.
Example Config
inputMode: 'differences', alternative: 'less', alpha: 0.01
Outcome
The calculator determines the rank sums and confirms with a Z-statistic that the optimization significantly reduced response times.

Try with Samples

math-&-numbers

Related Hubs

FAQ

What is the main difference between this and a paired t-test?

The Wilcoxon signed-rank test is nonparametric and does not require a normal distribution, whereas the paired t-test assumes the differences are normally distributed.

Can I use this test for independent samples?

No, this test is specifically for paired or related samples. For independent samples, use the Mann-Whitney U test.

How are zero differences handled in the calculation?

Pairs with a difference of zero are typically excluded from the ranking process, reducing the effective sample size.

What does a p-value lower than the alpha level mean?

It indicates that the observed difference is statistically significant, providing enough evidence to reject the null hypothesis.

Which input mode should I choose?

Use 'Paired Samples' if you have raw before/after data, or 'Differences' if you have already calculated the change for each pair.

API Documentation

Request Endpoint

POST /en/api/tools/wilcoxon-signed-rank-calculator

Request Parameters

Parameter Name Type Required Description
inputMode select No -
beforeValues textarea No -
afterValues textarea No -
differenceValues textarea No -
alternative select No -
alpha number No -
decimalPlaces number No -

Response Format

{
  "key": {...},
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}
JSON Data: JSON Data

AI MCP Documentation

Add this tool to your MCP server configuration:

{
  "mcpServers": {
    "elysiatools-wilcoxon-signed-rank-calculator": {
      "name": "wilcoxon-signed-rank-calculator",
      "description": "Run a paired nonparametric Wilcoxon signed-rank test from paired samples or differences",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=wilcoxon-signed-rank-calculator",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

You can chain multiple tools, e.g.: `https://elysiatools.com/mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp`, max 20 tools.

If you encounter any issues, please contact us at [email protected]