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Hypothesis Testing

Hypothesis testing is a statistical method used to make decisions about populations based on sample data. Use our comprehensive range of calculators to test claims about population parameters, compare groups, and determine statistical significance in your research.

Not sure which test to use?

Use our interactive tool to help you choose the right statistical test for your data:

Statistical Test Selector

Question 1 of 8

What type of data are you working with?

Categorical (e.g., categories, groups)

Numerical (e.g., measurements, counts)

Study Design & Power Analysis

Calculate the sample size needed for your study or experiment.

Sample Size Calculator Power Analysis Calculator Effect Size Calculator

Mean Comparisons (t-tests, Z-tests, Confidence Intervals)

Compare means between one or more groups, and compute confidence intervals.

One Sample t-test Two Sample t-test (Independent Samples)Paired Samples t-test (Dependent Samples)One Sample Z-Test Two Sample Z-Test

Proportion Comparisons (Z-tests, Confidence Intervals)

Compare proportions between groups and compute confidence intervals.

One Proportion Z-Test Two Proportion Z-Test

Non-Parametric Tests

Use non-parametric tests when data doesn’t meet normal distribution assumptions.

Mann-Whitney U Test Wilcoxon Signed Rank Test Kruskal-Wallis Test Friedman Test

Chi-Square and Categorical Data

Test relationships and goodness of fit for categorical data.

Chi-Square Goodness of Fit Test Chi-Square Test of Independence Fisher’s Exact Test

Analysis of Variance (ANOVA) and Post Hoc Analysis

Compare means and variances across multiple groups with various ANOVA techniques.

One-Way ANOVA Two-Way ANOVA Three-Way ANOVA Repeated Measures ANOVA Tukey’s HSD Test Dunnett’s Test Dunn’s Test ANCOVA (Analysis of Covariance)

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