Basic Python exercises

About the course
What are we doing?
Basic Python programming review
Polars and split-apply-combine
Data display
Probability: The foundation for generative modeling
- 20 Probability: definitions and interpretations
- 21 Probability distributions
Sampling out of probability distributions
Plug-in estimates and confidence intervals
Nonparametric inference with hacker stats
- 28 Performing bootstrap calculations
- 29 Pairs bootstrap and correlation
Null hypothesis significance testing
Generative modeling
- 33 Statistical modeling
- 34 Building a generative model
Parameter estimation
Variate-covariate models
Model assessment
Statistical watchouts
Basic Python exercises
Polars and split-apply-combine exercises
Data visualization exercises
Probability exercises
Nonparametric hacker stats exercises
- 71 Confidence intervals for microtubule catastrophe
- 72 Wrangling and hacker stats with Darwin’s finches
NHST exercises
- 73 NHST with Darwin’s finches
- 74 Dance of the p-values
Parameter estimation exercises I
Parameter estimation exercises II
- 78 Determining dissociation constants
- 79 MLE for a ligand-gated ion channel
Model assessment exercises
- 80 Analysis of microtubule catastrophe
- 81 Data transformations and parameter estimation

Basic Python exercises

In what follows, we unleash our Python programming skills on some (not-yet-statistical-inference) problems!

51 Dancing statistics

52 Using string methods{#exr-string-methods}

HUJI Stats 2025