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YouTube course using IPython and Jupyter notebooks to do statistical analysis.

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Chapter01_Audience_aim_motivation.html
Chapter01_Audience_aim_motivation.html
 
 
Chapter01_Audience_aim_motivation.ipynb
Chapter01_Audience_aim_motivation.ipynb
 
 
Chapter03_Why_python.html
Chapter03_Why_python.html
 
 
Chapter03_Why_python.ipynb
Chapter03_Why_python.ipynb
 
 
Chapter04_Introduction_to_the_IPython_Notebook-2.html
Chapter04_Introduction_to_the_IPython_Notebook-2.html
 
 
Chapter04_Introduction_to_the_IPython_Notebook.html
Chapter04_Introduction_to_the_IPython_Notebook.html
 
 
Chapter04_Introduction_to_the_IPython_Notebook.ipynb
Chapter04_Introduction_to_the_IPython_Notebook.ipynb
 
 
Chapter04_Introduction_to_the_IPython_Notebook.ipynbdnpp7x
Chapter04_Introduction_to_the_IPython_Notebook.ipynbdnpp7x
 
 
Chapter04_Introduction_to_the_IPython_Notebook_II.ipynb
Chapter04_Introduction_to_the_IPython_Notebook_II.ipynb
 
 
Chapter05_A_closer_look_at_our_data.html
Chapter05_A_closer_look_at_our_data.html
 
 
Chapter05_A_closer_look_at_our_data.ipynb
Chapter05_A_closer_look_at_our_data.ipynb
 
 
Chapter08_Research_types.html
Chapter08_Research_types.html
 
 
Chapter08_Research_types.ipynb
Chapter08_Research_types.ipynb
 
 
Chapter09_Data_types.html
Chapter09_Data_types.html
 
 
Chapter09_Data_types.ipynb
Chapter09_Data_types.ipynb
 
 
Chapter10_Introducing_pandas.html
Chapter10_Introducing_pandas.html
 
 
Chapter10_Introducing_pandas.ipynb
Chapter10_Introducing_pandas.ipynb
 
 
Chapter11_Measures_of_central_tendency_dispersion.html
Chapter11_Measures_of_central_tendency_dispersion.html
 
 
Chapter11_Measures_of_central_tendency_dispersion.ipynb
Chapter11_Measures_of_central_tendency_dispersion.ipynb
 
 
Chapter12_The_connection_between_probability_and_area.html
Chapter12_The_connection_between_probability_and_area.html
 
 
Chapter12_The_connection_between_probability_and_area.ipynb
Chapter12_The_connection_between_probability_and_area.ipynb
 
 
Chapter13_The_central_limit_theorem.html
Chapter13_The_central_limit_theorem.html
 
 
Chapter13_The_central_limit_theorem.ipynb
Chapter13_The_central_limit_theorem.ipynb
 
 
Chapter13_The_central_limit_theorem.ipynb3wgaui
Chapter13_The_central_limit_theorem.ipynb3wgaui
 
 
Chapter14_Z_and_t_distributions.html
Chapter14_Z_and_t_distributions.html
 
 
Chapter14_Z_and_t_distributions.ipynb
Chapter14_Z_and_t_distributions.ipynb
 
 
Chapter15_Hypotheses.html
Chapter15_Hypotheses.html
 
 
Chapter15_Hypotheses.ipynb
Chapter15_Hypotheses.ipynb
 
 
Chapter16_Confidence_intervals.html
Chapter16_Confidence_intervals.html
 
 
Chapter16_Confidence_intervals.ipynb
Chapter16_Confidence_intervals.ipynb
 
 
Chapter17_Parametric_non_tests.html
Chapter17_Parametric_non_tests.html
 
 
Chapter17_Parametric_non_tests.ipynb
Chapter17_Parametric_non_tests.ipynb
 
 
Chapter18_Comparing_means.html
Chapter18_Comparing_means.html
 
 
Chapter18_Comparing_means.ipynb
Chapter18_Comparing_means.ipynb
 
 
Chapter19_Comparing_categorical_data.html
Chapter19_Comparing_categorical_data.html
 
 
Chapter19_Comparing_categorical_data.ipynb
Chapter19_Comparing_categorical_data.ipynb
 
 
Chapter20_Linear_regression.html
Chapter20_Linear_regression.html
 
 
Chapter20_Linear_regression.ipynb
Chapter20_Linear_regression.ipynb
 
 
Chapter21_Sensitivity_specificity_risks_rates_odds.html
Chapter21_Sensitivity_specificity_risks_rates_odds.html
 
 
Chapter21_Sensitivity_specificity_risks_rates_odds.ipynb
Chapter21_Sensitivity_specificity_risks_rates_odds.ipynb
 
 
IPython_Notebook_Toolbar.png
IPython_Notebook_Toolbar.png
 
 
Launcher.png
Launcher.png
 
 
MOOC_Mock.csv
MOOC_Mock.csv
 
 
README.md
README.md
 
 
Regression.csv
Regression.csv
 
 
Toolbar.png
Toolbar.png
 
 
odds_ratio.csv
odds_ratio.csv
 
 
p_graph.png
p_graph.png
 
 
style.css
style.css
 
 
wcc_crp.xlsx
wcc_crp.xlsx
 
 

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Python_for_Medical_Statistics

YouTube course using IPython and Jupyter notebooks to do statistical analysis.

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YouTube course using IPython and Jupyter notebooks to do statistical analysis.

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