1. What Is Chi Square Distribution?

The Chi Square distribution is a statistical distribution used primarily in hypothesis testing, particularly for categorical data analysis. It measures how observed data compares to expected data under a specific hypothesis.

2. How Does The Calculator Work?

The calculator uses the Chi Square formula:

Where:

• \( O \) — Observed frequency values
• \( E \) — Expected frequency values
• \( \sum \) — Summation across all categories

Explanation: The formula calculates the sum of squared differences between observed and expected values, divided by expected values for each category.

3. Importance Of Chi Square Test

Details: Chi Square tests are essential for determining whether there's a significant association between categorical variables, testing goodness of fit, and checking independence in contingency tables.

4. Using The Calculator

Tips: Enter observed and expected values as comma-separated lists. Both lists must contain the same number of values and all values must be positive numbers.

5. Frequently Asked Questions (FAQ)

Q1: When should I use a Chi Square test?
A: Use it when you have categorical data and want to test hypotheses about distributions or associations between variables.

Q2: What does a high Chi Square value indicate?
A: A high Chi Square value suggests a significant difference between observed and expected values, potentially leading to rejection of the null hypothesis.

Q3: What are the assumptions of the Chi Square test?
A: The test assumes independence of observations, adequate sample size, and expected frequencies of at least 5 in each category.

Q4: Can Chi Square be used for small sample sizes?
A: For small samples, Fisher's exact test is often more appropriate as Chi Square may not be valid with expected frequencies below 5.

Q5: How do I interpret the p-value from a Chi Square test?
A: A p-value less than your significance level (typically 0.05) indicates that the observed differences are statistically significant.