04-05: Distribution Analyzer

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Generates 2000 random samples from four distributions (Normal, Uniform, Exponential, Binomial) and plots each as a histogram with mean line, ±1σ lines, shaded IQR, and a stats text box. A second figure overlays all four normalised distributions for comparison.

Topics covered: np.random.normal/uniform/exponential/binomial · ax.hist(density=True) · ax.axvline() · ax.axvspan() · np.percentile() · ax.text() with bbox · fig.add_subplot()

Difficulty: ⭐⭐ Intermediate

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Requirements

pip install matplotlib numpy

How to Run

python main.py

Outputs: distributions.png, distributions_overlay.png

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Key Concepts Practised

Concept	Where used
np.random.normal(loc=70, scale=15)	Normal distribution
ax.hist(bins=30, density=False)	Frequency histogram
ax.hist(density=True)	Normalised (comparable) histogram
ax.axvline(mean)	Mean marker line
ax.axvspan(q25, q75)	Shaded IQR region
ax.text(transform=ax.transAxes)	Stats box in axes coordinates