Statistics & Probability for Analytics Interviews is a structured track of 13 lessons that build a complete, interview-ready understanding of the topic. Work through them in order, then use the quiz and flashcards in each lesson to revise.
What this course covers
- Descriptive Statistics: Centre, Spread & Shape - Mean, median, variance, standard deviation and skew, and what each hides.
- When the Average Lies: Skew, Outliers & Median vs Mean - Why the mean misleads on skewed business data, with Indian salary and order-value examples.
- Probability Essentials: Rules, Conditional Probability & Bayes' Theorem - The probability an analyst is tested on, including a worked Bayes calculation.
- The Distributions Analysts Actually Use - Normal, binomial, Poisson and power-law, each matched to the data it describes.
- Sampling, Sampling Bias & the Central Limit Theorem - How samples go wrong, and why sample means behave predictably even when data does not.
- Confidence Intervals & Margin of Error, Explained Plainly - What a confidence interval does and does not claim, and how to report one.
- Hypothesis Testing: Null, Alternative, p-Values & Significance - The full testing logic, and the correct one-sentence interpretation of a p-value.
- Type I & Type II Errors, Statistical Power and Sample Size - Both error types, the business cost of each, and how power drives sample size.
- Choosing the Right Test: t-Test, Chi-Square & Analysis of Variance - A decision tree from data type and group count to the correct test.
- Non-Parametric Tests: What to Use When Assumptions Break - Rank-based alternatives for when normality or equal variance fails.
- Correlation, Regression & the Limits of Both - Reading correlation and a fitted line honestly, including where both break down.
- Correlation vs Causation: Confounders & Study Design - Confounding, spurious correlation, and the designs that support a causal claim.
- Statistical Traps: p-Hacking, Multiple Comparisons & Simpson's Paradox - How analyses go wrong invisibly, each shown with a reversal you can reproduce.