{"id":25527515,"url":"https://github.com/jacekkala/statistics_hypothesis_testing","last_synced_at":"2026-02-11T11:01:42.797Z","repository":{"id":249284793,"uuid":"831096149","full_name":"jacekkala/statistics_hypothesis_testing","owner":"jacekkala","description":"Statistics \u0026 Hypothesis Testing in Python","archived":false,"fork":false,"pushed_at":"2025-02-02T10:51:03.000Z","size":4095,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-22T02:08:12.251Z","etag":null,"topics":["charts","hypothesis-testing","jupyter-notebook","matplotlib","numpy","pandas","python","scipy-stats","seaborn","statistics"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jacekkala.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-07-19T16:43:25.000Z","updated_at":"2025-02-02T22:05:11.000Z","dependencies_parsed_at":"2025-02-06T10:34:34.754Z","dependency_job_id":null,"html_url":"https://github.com/jacekkala/statistics_hypothesis_testing","commit_stats":null,"previous_names":["jankiel-predator/statistics","jacekkala/statistics_hypothesis_testing"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jacekkala/statistics_hypothesis_testing","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacekkala%2Fstatistics_hypothesis_testing","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacekkala%2Fstatistics_hypothesis_testing/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacekkala%2Fstatistics_hypothesis_testing/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacekkala%2Fstatistics_hypothesis_testing/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jacekkala","download_url":"https://codeload.github.com/jacekkala/statistics_hypothesis_testing/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacekkala%2Fstatistics_hypothesis_testing/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29332292,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-11T06:13:03.264Z","status":"ssl_error","status_checked_at":"2026-02-11T06:12:55.843Z","response_time":97,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["charts","hypothesis-testing","jupyter-notebook","matplotlib","numpy","pandas","python","scipy-stats","seaborn","statistics"],"created_at":"2025-02-19T22:19:21.492Z","updated_at":"2026-02-11T11:01:42.776Z","avatar_url":"https://github.com/jacekkala.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📊 Statistics \u0026 Hypothesis Testing in Python using Jupyter Notebooks\n\nWelcome to the **Statistics \u0026 Hypothesis Testing in Python** repository! This collection of Jupyter Notebooks offers an in-depth exploration of various statistical concepts and hypothesis testing techniques, all presented in a visually appealing and comprehensive manner.\n\n## 📚 Notebooks Overview\n\nEach notebook in this repository is meticulously crafted, providing:\n- **Rich Descriptions**: Clear objectives, theoretical background, and conclusions for each experiment.\n- **Beautiful Visualizations**: A wide range of charts and visual aids that are not only informative but also aesthetically pleasing.\n\n## 🌟 Highlights\n\n- **Engaging Visuals**: Each notebook is packed with charts and graphs that are not only functional but also crafted to be visually appealing.\n- **Comprehensive Coverage**: From basic concepts to advanced hypothesis testing methods, this repository covers a broad spectrum of topics.\n- **Educational Value**: Detailed explanations and clear objectives make it easy to understand the purpose and outcomes of each experiment.\n\n## 📁 Repository Contents\n\nHere's a breakdown of the notebooks included in this repository:\n\n1. **Introduction**\n   - Understanding dataset structure\n   - Selecting subsets of columns\n   - Constructing histograms and dotplots\n\n2. **Sampling Methods**\n   - Applying sampling methods\n   - Evaluating sample representativeness\n3. **Visualizing Data**\n   - Creating Bar Charts, Pie Charts, Stem-And-Leaf Plots, Histograms\n4. **Descriptive Statistics**\n   - Determining numerical characteristics\n   - Constructing boxplots\n5. **Correlation**\n   - Generating scatterplots\n   - Computing correlation coefficients\n6. **Linear Regression**\n   - Performing correlation and regression analysis\n7. **Multiple Linear Regression**\n   - Constructing and evaluating models\n   - Interpreting coefficients\n   - Diagnosing multicollinearity\n8. **Logistic Regression**\n   - Implementing logistic regression\n   - Performing classification\n9. **Examining Normality**\n   - Assessing normality using QQ-plots\n10. **Central Limit Theorem**\n    - Investigating the Central Limit Theorem\n    - Using uniform and exponential distributions\n11. **Properties of Probability Estimation**\n    - Exploring probability estimation\n12. **Bootstrap**\n    - Learning the bootstrap method\n13. **Student's t-Test**\n    - Applying Student's t-distribution\n    - Comparing sample means\n14. **Single Sample Population Mean Test**\n    - Testing population means\n    - Assessing evidence against null hypotheses\n15. **One Sample Proportion Test**\n    - Conducting one-sample proportion tests\n    - Analyzing model data\n16. **Standard Vs Welch's t-Test**\n    - Testing means for two samples\n    - Comparing variances\n17. **Paired t-Test**\n    - Conducting paired t-tests\n    - Assessing population mean differences\n18. **Independent Samples Proportions Z-test**\n    - Testing differences in proportions\n19. **Density \u0026 Distribution Functions**\n    - Comparing empirical and theoretical probability functions\n20. **Chi-Squared Goodness of Fit Test**\n    - Understanding chi-square goodness of fit\n21. **Kolmogorov-Smirnov Test**\n    - Applying Kolmogorov-Smirnov tests\n22. **Tests on Normality**\n    - Assessing sample data normality\n    - Using Q-Q plots and various tests\n23. **Relationship Between Categorical Variables**\n    - Testing relationships using Chi-squared and Fisher's Exact Test\n24. **Association Between Two Binary Variables**\n    - Testing and measuring associations\n25. **Analysis of Variance (ANOVA)**\n    - Conducting one-factor ANOVA\n    - Interpreting results\n   \n## 🔍 Explore and Learn\n\nDive into the notebooks to explore various statistical methods and hypothesis tests. Whether you're a beginner looking to learn the basics or an advanced user seeking to deepen your understanding, this repository has something for everyone.\n\nHappy Learning! 🎓\n\n---\n\nFeel free to reach out if you have any questions or suggestions. Contributions are always welcome!\n\n---\n\n[![GitHub license](https://img.shields.io/github/license/Jankiel-Predator/Statistics)](https://github.com/Jankiel-Predator/Statistics/blob/main/LICENSE)\n[![GitHub stars](https://img.shields.io/github/stars/Jankiel-Predator/Statistics)](https://github.com/Jankiel-Predator/Statistics/stargazers)\n[![GitHub forks](https://img.shields.io/github/forks/Jankiel-Predator/Statistics)](https://github.com/Jankiel-Predator/Statistics/network)\n\n---\n\n### 📬 Contact\n\n- GitHub: [@Jankiel-Predator](https://github.com/Jankiel-Predator)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjacekkala%2Fstatistics_hypothesis_testing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjacekkala%2Fstatistics_hypothesis_testing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjacekkala%2Fstatistics_hypothesis_testing/lists"}