{"id":14989215,"url":"https://github.com/pegah-ardehkhani/statistics-and-probability-in-python","last_synced_at":"2025-04-05T05:08:40.769Z","repository":{"id":37385392,"uuid":"503522879","full_name":"Pegah-Ardehkhani/Statistics-and-Probability-in-Python","owner":"Pegah-Ardehkhani","description":"A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Statistics and Probability in Python 📊 📈 ![license](https://img.shields.io/github/license/Pegah-Ardehkhani/Statistics-and-Probability-in-Python.svg) ![releases](https://img.shields.io/github/release/Pegah-Ardehkhani/Statistics-and-Probability-in-Python.svg)\n\n\u003e **`Note`**: This repository is still developing.\n\n\u003cp align=\"center\"\u003e \n  \u003cimg width=\"500\" height=\"350\" src=\"https://cdn.dribbble.com/users/962944/screenshots/14138307/media/ca3377660c3d2053c9d91ac175871429.gif\"\u003e \n\u003c/p\u003e\n\n## Table of content ✍️\n\n**Chapter 1: Special Continuous Random Variables** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%201%20Special%20Continuous%20Random%20Variables.ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%201%20Special%20Continuous%20Random%20Variables.ipynb)\n\n- 1.1. Normal (Gaussian) Distribution\n- 1.2. Chi-square Distribution\n- 1.3. T-student Distribution\n- 1.4. Fisher Distribution\n- 1.5. Continuous Uniform Distribution\n- 1.6. Exponential Distribution\n- 1.7. Gamma Distribution\n- 1.8. Beta Distribution\n- 1.9. Weibull Distribution\n- 1.10. Cauchy Distribution\n- 1.11. Laplace Distribution\n- 1.12. Logistic Distribution\n\n**Chapter 2: Special Discrete Random Variables** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%202%20Special%20Discrete%20Random%20Variables.ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%202%20Special%20Discrete%20Random%20Variables.ipynb)\n\n- 2.1. Bernoulli Distribution\n- 2.2. Binomial Distribution\n- 2.3. Negative Binomial (Pascal) Distribution\n- 2.4. Geometric Distribution\n- 2.5. Poisson Distribution\n- 2.6. Discrete Uniform Distribution\n- 2.7. Hypergeometric Distribution\n\n**Chapter 3: Confidence Intervals** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%203%20Confidence%20Intervals.ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%203%20Confidence%20Intervals.ipynb)\n\n- 3.1. Confidence Interval for the Mean of a Normal Population\n  - 3.1.1. Known Standard Deviation\n  - 3.1.2. Unknown Standard Deviation\n- 3.2. Confidence Interval for the Variance of a Normal Population\n  - 3.2.1. Unknown Mean of the Population\n  - 3.2.2. Known Mean of the Population\n- 3.3. Confidence Interval for the Difference in Means of Two Normal Population\n  - 3.3.1. Known Variances\n  - 3.3.2. Unknown but Equal Variances\n- 3.4. Confidence Interval for the Ratio of Variances of Two Normal Populations\n- 3.5. Confidence Interval for the Mean of a Bernoulli Random Variable\n\n**Chapter 4: Parametric Hypothesis Testing** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%204%20Parametric%20Hypothesis%20Testing.ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%204%20Parametric%20Hypothesis%20Testing.ipynb)\n\n- 4.1. Introduction\n- 4.2. Test Concerning the Mean of a Normal Population\n  - 4.2.1. Known Standard Deviation\n  - 4.2.2. Unknown Standard Deviation\n- 4.3. Test Concerning the Equality of Means of Two Normal Populations\n  - 4.3.1. Known Variances\n  - 4.3.2. Unknown but Equal Variances\n- 4.4. Paired t-test\n- 4.5. Test Concerning the Variance of a Normal Population\n- 4.6. Test Concerning the Equality of Variances of Two Normal Populations\n- 4.7. Test Concerning P in Bernoulli Populations\n- 4.8. Test Concerning the Equality of P in Two Bernoulli Populations\n\n**Chapter 5: Statistical Hypothesis Testing** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%205%20Statistical%20Hypothesis%20Testing.ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%205%20Statistical%20Hypothesis%20Testing.ipynb)\n\n- 5.1. Normality Tests\n  - 5.1.1. Shapiro-Wilk Test\n  - 5.1.2. D’Agostino’s  Test\n  - 5.1.3. Anderson-Darling Test\n- 5.2. Correlation Tests\n  - 5.2.1. Pearson’s Correlation Coefficient\n  - 5.2.2. Spearman’s Rank Correlation\n  - 5.2.3. Kendall’s Rank Correlation\n  - 5.2.4. Chi-Squared Test\n- 5.3. Stationary Tests\n  - 5.3.1. Augmented Dickey-Fuller Unit Root Test\n  - 5.3.2. Kwiatkowski-Phillips-Schmidt-Shin Test\n- 5.4. Other Tests\n  - 5.4.1. Mann-Whitney U-Test\n  - 5.4.2. Wilcoxon Signed-Rank Test\n  - 5.4.3. Kruskal-Wallis H Test\n  - 5.4.4. Friedman Test\n\n**Chapter 6: Regression** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%206%20Regression.ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%206%20Regression.ipynb)\n\n- 6.1. Introduction\n- 6.2. Least Squares Estimators of the Regression Parameters\n- 6.3. Statistical Inferences about the Regression Parameters\n  - 6.3.1. Inferences Concerning  B \n    - 6.3.1.1. Known Variance\n    - 6.3.1.2. Unknown Variance\n  - 6.3.2. Inferences Concerning  A \n    - 6.3.2.1. Unknown Variance\n  - 6.3.3. T-tests for Regression Parameters with statsmodels\n  - 6.3.4. F-statistic for Overall Significance in Regression\n- 6.4. Confidence Intervals Concerning Regression Models\n  - 6.4.1. Confidence Interval for  B \n    - 6.4.1.1. Known Variance\n    - 6.4.1.2. Unknown Variance\n  - 6.4.2. Confidence Interval for  A \n    - 6.4.2.1. Unknown Variance\n  - 6.4.3. Confidence Interval for  A+Bx \n    - 6.4.3.1. Unknown Variance\n  - 6.4.4. Prediction Interval of a Future Response\n- 6.5. Residuals\n  - 6.5.1. Regression Diagnostic\n  - 6.5.2. Multicollinearity\n\n**Chapter 7: Analysis of Variance (ANOVA)** \u003ca href=\"https://colab.research.google.com/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%207%20Analysis%20of%20Variance%20(Anova).ipynb\" target=\"_parent\\\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/\u003e\u003c/a\u003e [![nbviewer](https://img.shields.io/badge/render-nbviewer-orange.svg)](http://nbviewer.org/github/Pegah-Ardehkhani/Statistics-and-Probability-in-Python/blob/main/Chapter%207%20Analysis%20of%20Variance%20%28Anova%29.ipynb)\n\n- 7.1. One-Way Analysis of Variance\n  - 7.1.1. Equal Sample Sizes\n  - 7.1.2. Unequal Sample Sizes\n- 7.2. Two-Way Analysis of Variance\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpegah-ardehkhani%2Fstatistics-and-probability-in-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpegah-ardehkhani%2Fstatistics-and-probability-in-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpegah-ardehkhani%2Fstatistics-and-probability-in-python/lists"}