Subjects

Descriptive Statistics & Exploratory Data Analysis

Learn to describe centre, spread and shape, choose the right plot for the question, detect outliers and missing-data mechanisms, run data quality checks that catch leakage and unit errors, avoid Simpson's paradox, and follow a repeatable EDA checklist in pandas.

Probability Fundamentals

Master conditional probability, Bayes' theorem and the base-rate fallacy, random variables, expectation and variance, the six distributions data scientists actually meet, the Law of Large Numbers and Central Limit Theorem, and the classic interview puzzles.