Chi Square Graphpad Verified -

Beyond the P-Value: How to Get a "Verified" Chi-Square Test in GraphPad Prism

• Formula: $(Rows - 1) \times (Columns - 1)$.
• For a standard 2x2 table, $df = 1$.

1. Test the association between two categorical variables: For example, to determine if there is a relationship between the type of treatment and the outcome of a disease.
2. Compare observed frequencies with expected frequencies: For example, to determine if the observed frequencies of a certain event are significantly different from the expected frequencies.

Why Verify Chi Square Test Results?

• Treatment1: A=10, B=20
• Treatment2: A=30, B=10
• Treatment3: A=20, B=10 Totals:
• Row totals and column totals computed; compute Eij = (row_i × col_j)/N Compute χ² by summing (O−E)²/E across all 6 cells, get df = (3−1)(2−1) = 2, then P from chi-square CDF. Verify with chisq.test in R or chi2_contingency in Python.

Verifying Chi Square Test Results using GraphPad: A Step-by-Step Guide

1. Click the "Analyze" button in the toolbar.
2. In the analysis dialog, select "Contingency table analysis".
3. Ensure your data table is selected, then click OK.

Because the confidence interval does not include 1.0, it confirms the statistical significance.

1. Categorical Data: Your variables are categories (e.g., Treated vs. Control; Survived vs. Died; Yes vs. No).
2. Independence: Each subject contributes to only one cell in the table.
3. Sample Size: The expected value for each cell should generally be greater than 5. If you have small sample sizes, Prism will suggest Fisher’s Exact Test instead.