The 20_probability/ module currently has no interactive widgets. Distribution-parameter sliders are a natural fit — they're one of the textbook examples of "vary a parameter, see the shape change" that ipywidgets is designed for.
Scope
Targets: 20_probability/10_probability.ipynb, 20_probability/15_generating_random_numbers.ipynb, 20_probability/20_statistics.ipynb. Pick a subset for a first PR.
Per notebook: pick the central distribution covered and add sliders for its shape parameters, re-rendering the PDF (and CDF) as the user moves the sliders.
- Normal: μ, σ → bell curve; show how σ stretches and μ shifts.
- Binomial: n, p → discrete bars approaching normal as n grows (CLT preview).
- Poisson: λ → discrete bars; show approach to normal for large λ.
- Exponential: λ → memoryless decay.
Optional: empirical histogram from numpy.random overlaid on the analytic PDF, with a sample-size slider showing the histogram converging.
Why
Distribution shape vs parameter is the foundational intuition of probability. Sliders carry it directly; tables don't. The empirical-overlay variant also previews the law of large numbers without naming it.
Validated slider pattern (#353/#354). The module has no widgets today, so this is a whole-module uplift rather than a notebook-by-notebook fix — one PR can probably cover all three target notebooks.
The
20_probability/module currently has no interactive widgets. Distribution-parameter sliders are a natural fit — they're one of the textbook examples of "vary a parameter, see the shape change" that ipywidgets is designed for.Scope
Targets:
20_probability/10_probability.ipynb,20_probability/15_generating_random_numbers.ipynb,20_probability/20_statistics.ipynb. Pick a subset for a first PR.Per notebook: pick the central distribution covered and add sliders for its shape parameters, re-rendering the PDF (and CDF) as the user moves the sliders.
Optional: empirical histogram from
numpy.randomoverlaid on the analytic PDF, with a sample-size slider showing the histogram converging.Why
Distribution shape vs parameter is the foundational intuition of probability. Sliders carry it directly; tables don't. The empirical-overlay variant also previews the law of large numbers without naming it.
Validated slider pattern (#353/#354). The module has no widgets today, so this is a whole-module uplift rather than a notebook-by-notebook fix — one PR can probably cover all three target notebooks.