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📚 Python for Introductory Statistics
Chapters ▾
0. Why Learn Python?1. Introduction to Python2. Python Lists3. Python Syntax4. Python Loops5. Frequency Distributions and Graphs6. Measures of Center and Variation7. Measures of Position8. Discrete Probability Distributions9. Continuous Probability Distributions10. Confidence Intervals11. Hypothesis Testing12. Linear Regression and Correlation13. Analysis of Categorical Data14. Advanced Statistics TopicsAppendix 1: Python Installing StepsAppendix 2: Random Integer GeneratorAppendix 3: Counting, Permutations and CombinationsCode ReferencesResources

11. Hypothesis Testing

Hypothesis testing involves making decisions on a claim or statement made about the value of population parameter.

First, the claim is used to define the null Ho and alternative Ha hypotheses. The alternative hypothesis is used to determine if the test is left (smaller), right (greater) or two-tailed test. A test-statistic and p-value are calculated with the assumption that the null hypothesis is true. A significant level or rejection region can be used to make a decision about the null-hypothesis.

Adapted from Python for Introductory Statistics, by Simon Aman (Truman College, City Colleges of Chicago), licensed under CC BY 4.0. Changes were made: reformatted as an accessible XYZ web edition with live in-browser code cells. License: CC-BY-4.0.