Probability and Statistics with Python

Apply fundamental counting principles, including permutations and combinations.

Calculate probabilities using axioms, conditional probability, and Bayes' theorem.

Differentiate between discrete and continuous random variables and their distributions (PMF/PDF).

Calculate and interpret the expected value and variance of random variables.

Model scenarios using Bernoulli, Binomial, and Poisson distributions.

Model scenarios using Uniform, Exponential, and Normal distributions.

Compute and interpret descriptive statistics (mean, median, variance) for a dataset using Pandas.

Create and interpret histograms, box plots, and scatter plots using Matplotlib and Seaborn.