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Python Inferential Statistics/ Linear & Logistic Regression Tutorials

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Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
Phase1_Report_Sample.ipynb		Phase1_Report_Sample.ipynb
README.md		README.md
Stats_Phase2_Report_Template.ipynb		Stats_Phase2_Report_Template.ipynb
ch1n2_intro_to_data.ipynb		ch1n2_intro_to_data.ipynb
ch3_probability.ipynb		ch3_probability.ipynb
ch4_normal_distribution.ipynb		ch4_normal_distribution.ipynb
ch5_confidence_intervals.ipynb		ch5_confidence_intervals.ipynb
ch5_sampling_distributions.ipynb		ch5_sampling_distributions.ipynb
ch6_inf_for_categorical_data.ipynb		ch6_inf_for_categorical_data.ipynb
ch7_inf_for_numerical_data.ipynb		ch7_inf_for_numerical_data.ipynb
ch8_simple_regression.ipynb		ch8_simple_regression.ipynb
ch9_multiple_regression.ipynb		ch9_multiple_regression.ipynb
custom.css		custom.css
custom_css_how_to.txt		custom_css_how_to.txt
histQQmatch.png		histQQmatch.png
regression_case_study_predicting_age_in_census_data.ipynb		regression_case_study_predicting_age_in_census_data.ipynb

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OpenIntro Labs for Python

This repository is a collection of tutorials to teach how to do data analysis with Python based on OpenIntro Statistics, a free and open-source textbook. The source files are processed using the Jupyter Notebook. These have been tested with Python 3.11.