Module 2: statistical inference for data science

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Content

Folder with all notebooks here

Day 1

• slides
• notebook descriptive statistics: pdf, html, ipynb
• notebook probability: pdf, html, ipynb

Day 2

• slides: parameter estimation
• notebook regression: pdf, pdf-v2, html, ipynb, ipynb-v2

Day 3

• slides
• notebook hypothesis testing: pdf, html, ipynb

Day 4

• notebook statistics summary: pdf, html, ipynb

Older:

1. descriptive statistics (jupyter notebook, html version)
2. probability and descriptive statistics (jupyter notebook, html version)
3. parameter estimation / regression (jupyter notebook, html version)
   • linear regression - Non-linear regression - Non-parametric regression
4. hypothesis Testing (jupyter notebook, html version)
   • vocabulary and an example - Normality tests - Non-parametric Wilcoxon signed rank test - ANOVA tests
5. project work example (jupyter notebook, html version)

Contact

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