Learn how two-tailed tests determine statistical significance in hypothesis testing by evaluating if a sample differs from a population mean. Discover real-world applications.

The (modest) goal of hypothesis testing is to reduce the directly-relevant data to a “level of suspicion” based purely on the data. That level of suspicion can then be combined (outside of hypothesis ...

Hypothesis Testing 4--Chi-Square for Goodness of Fit Tests and Independence In Hypothesis Testing 1, 2 and 3, you have used normal and t-distributions to test hypotheses. Chi-Square tests use the ...

Beta risk is the probability that a false null hypothesis will be accepted by a statistical test.

In this article, we explore the theory, assumptions and interpretation of the Fisher’s exact test, used to investigate associations between two categorical, binary variables with small sample sizes, ...

The Brookbush Institute continues to enhance education with new courses, a modern glossary, an AI Tutor, and a client pr ...

The problem of hypothesis testing about proportions in two finite populations is addressed. The usual test based on the normal approximation (Z test) and a test based on estimated p values (E test) ...