What is hypothesis testing?

Hypothesis testing is a statistical method to decide whether sample data provides enough evidence to reject a claim (null hypothesis) about a population. You compare a test statistic to a critical value or use a p-value.

When should I use a z-test vs a t-test?

Use a z-test when the population standard deviation is known and the sample size is large (n > 30). Use a t-test when the population standard deviation is unknown and you estimate it with the sample standard deviation, especially for small samples.

What does the p-value mean?

The p-value is the probability of observing results as extreme as the sample data, assuming the null hypothesis is true. A small p-value (typically < 0.05) suggests the null hypothesis should be rejected.

Hypothesis Testing Calculator

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About Hypothesis Testing Calculator

Run z-tests, t-tests, two-sample t-tests, and chi-square tests with detailed step-by-step solutions. The calculator states the null and alternative hypotheses, computes the test statistic, finds the p-value, and explains the conclusion in plain language.

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FAQ

Is this statistics calculator free?

Yes! The Statistics Calculator provides free step-by-step solutions for descriptive statistics, z-scores, probability distributions, and hypothesis tests. No account required.

What types of statistics problems can it calculate?

It covers descriptive statistics (mean, median, mode, standard deviation, quartiles), z-score calculations with probability lookups, normal and t-distributions, and hypothesis tests including z-tests, t-tests, and proportion tests.

How are the step-by-step solutions generated?

Solutions are generated using scipy.stats and precise mathematical formulas. Unlike AI chatbots, every calculation is deterministic and mathematically guaranteed to be correct.

Can I see graphs and distribution curves?

Yes! Solutions include visual bell curves with shaded probability regions, making it easy to understand z-scores, p-values, and distribution areas at a glance.

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