Test of Hypotheses: 100 Tips and Strategies for Effective Hypothesis Testing

Photo by Faris Mohammed on Unsplash

Hypothesis testing is a fundamental concept in statistics, used to make inferences about population parameters based on sample data. Here are 100 tips for tests of hypotheses:

1. Basics of Hypothesis Testing:

1. Null Hypothesis (H₀): The default assumption that there is no effect or no difference.
2. Alternative Hypothesis (H₁): The claim that contradicts the null hypothesis.
3. Type I Error (α): Incorrectly rejecting a true null hypothesis.
4. Type II Error (β): Failing to reject a false null hypothesis.
5. Significance Level (α): The threshold for rejecting the null hypothesis (common values include 0.05, 0.01).

2. One-Sample Tests:

1. One-Sample t-Test: Compare the mean of a single sample to a known or hypothesized population mean.
2. One-Sample z-Test: Similar to the t-test, but used when the population standard deviation is known.
3. Wilcoxon Signed-Rank Test: Non-parametric alternative to the one-sample t-test for comparing medians.

3. Two-Sample Tests:

1. Independent Samples t-Test: Compare means of two…