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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

10. Confidence Intervals

Inferential statistics deals with making inferences about a population parameter using information contained in the sample. Estimation and Hypothesis testing are two types of inferential statistics. There are two types of estimation: point and interval estimation.

  1. The sample mean x¯ is a point estimate of the population mean μ
  2. The sample proportion p^ is a point estimate of the population proportion p.

An interval estimate or confidence interval provides two values, where all real numbers between these values are considered as an estimate to the population parameter.

  1. (x¯−E,x¯+E) interval estimate of the mean μ
  2. (p^−E,p^+E) interval estimate of the proportion p

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.