What you'll learn

50 lessons in Statistics

Descriptive statisticsData displays & box plotsComparing distributionsTwo-way tablesScatterplots & correlation in contextz-scores & standardizingThe normal distribution & empirical ruleSampling methods & biasConfidence interval for a proportion & margin of errort vs z: the one-sample t-introHypothesis testingLinear regressionSampling distributionsConfidence intervalsThe two-sample t-testANOVA: comparing group meansCorrelation vs causationMaximum likelihood estimationMethod of momentsChi-square testsBootstrap & resamplingSufficient statisticsPoint estimation: bias, MSE & consistencyFisher information & the Cramér–Rao boundExponential familiesMCMC: Metropolis-Hastings & GibbsGeneralized linear models (GLMs)Proof: OLS minimizes squared errorProof: unbiasedness of $s^2$Sketch: Central Limit TheoremMultivariate statistics: PCA, factor analysisTime series basicsThe Cramér–Rao lower boundThe Neyman–Pearson lemmaConjugate priors & Bayesian estimationNonparametric testsMultiple testing: Bonferroni & FDRExperimental designSurvival analysis & Kaplan–MeierStatistical decision theoryAsymptotic statistics & the delta methodThe EM algorithmCausal inferenceStatistical learning theoryRobust statisticsSequential analysis & the SPRTModel selection: AIC, BIC & cross-validationPower & sample sizeResidual analysis & regression diagnosticsThe Rao–Blackwell theorem

How Erudia teaches

Built to be understood — and remembered.

Every idea is taught with motivation and a worked example before the drills, and an FSRS spaced-repetition engine schedules each review for the day its model predicts you would forget it. A short placement check finds what you already know, so you start Statistics exactly where it's useful.

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Related Probability & Statistics subjects

Probability Stochastic Processes Game Theory Information & Coding Theory Random Matrix Theory Quantitative Problem-Solving