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Mastering the Chi-Square Test in GraphPad Prism: A Step-by-Step Guide

The Chi-Square ($\chi^2$) test is a fundamental statistical tool used to determine if there is a significant association between categorical variables. While it can be calculated by hand, GraphPad Prism is one of the most trusted tools for performing this analysis quickly and generating publication-quality graphs.

This guide focuses on the Chi-Square Test of Independence (also known as the Contingency Table Chi-Square), which is the most common application in biological and medical research. chi square graphpad verified

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3. Running the analysis

1. Click Analyze (top toolbar).
2. Select Contingency table analysis.
3. Under Parameters:
   • Chi-square – Check the box.
   • For 2×2 tables, also check Fisher's exact test (recommended if any expected count <5).
   • Yates’ continuity correction – generally optional (GraphPad default is without it).

Short summary

Use GraphPad Prism to run chi-square tests and report results clearly and reproducibly. Below is a concise, publication-ready template with steps, output interpretation, and example wording. Mastering the Chi-Square Test in GraphPad Prism: A

Part 2: Entering Data into GraphPad Prism

1. Open GraphPad Prism.
2. Upon opening, you will see the "Welcome" dialog.
3. Select the Contingency table option from the column on the left.
4. Ensure "Enter: No enter or import data" is selected (or "Start with an empty data table").
5. Click Create.

Inputting the Numbers: In the data table, you will see a grid. You do not need to enter raw data (rows of individual subjects). Instead, enter the counts (frequencies). Click Analyze (top toolbar)

• Rows: Usually define the outcomes (e.g., Survived / Died).
• Columns: Usually define the groups (e.g., Treatment / Control).

Example Data Set: | | Treatment (Col A) | Control (Col B) | | :--- | :--- | :--- | | Outcome: Yes | 45 | 30 | | Outcome: No | 10 | 25 |

Enter your numbers exactly as they appear in your contingency table.

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Steps to reproduce in GraphPad Prism

1. Enter data:
   • For goodness-of-fit: one column with observed counts and a second column with expected proportions or counts.
   • For contingency table: create a table with rows = groups and columns = categories; fill cells with counts.
2. Choose analysis:
   • Goodness-of-fit: Analyze → Column analyses → Chi-square goodness-of-fit.
   • Contingency table: Analyze → Contingency table analyses → Chi-square test (or Fisher's exact if expected counts <5).
3. Set options:
   • Use Yates’ continuity correction only for 2×2 tables if desired (report if applied).
   • For expected counts: let Prism compute expected values from marginal totals for contingency tables.
4. Run analysis and export:
   • Save the results table and chi-square summary.
   • Export the observed vs. expected table and test summary (χ2, df, P value, any corrections).