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Bonferroni correction – What It Is and Why It Matters

The Bonferroni correction is a statistical method used to reduce the risk of Type I errors (false positives) when you run multiple hypothesis tests. Every time you test a hypothesis, there’s a chance you’ll incorrectly… 

Type I and type II errors

Type I Error (False Positive) You reject a true null hypothesis — you conclude something is happening when it actually isn’t. Example:A medical test says a patient has a disease, but they actually don’t. Type… 

independent samples in hypothesis testing

🧩 What “Independent Samples” Means Two samples are independent when the individuals in one group have no relationship to the individuals in the other group. This is the setup for the independent‑samples t‑test, also called… 

One sample t-test

A one‑sample t‑test checks whether the mean of a single sample is significantly different from a known or hypothesized population mean. It answers the question: “Is my sample mean different enough from the population mean… 

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