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Binomial, Poisson, Normal, Gamma, and Beta distributions.
| Chapter | Topic | |---------|-------| | 1 | Probability axioms, sample spaces, combinatorics | | 2 | Random variables (discrete & continuous) | | 3 | Mathematical expectation, moments, moment-generating functions | | 4 | Special distributions (binomial, Poisson, normal, gamma, beta) | | 5 | Multivariate distributions – joint, marginal, conditional | | 6 | Functions of random variables (CDF, transformation techniques) | | 7 | Sampling distributions (chi-square, t, F) | | 8 | Convergence in probability – LLN, CLT | | 9 | Point estimation – MLE, method of moments, unbiasedness | | 10 | Interval estimation & hypothesis testing (Neyman-Pearson lemma) | | 11 | Sufficiency, completeness, Rao-Blackwell theorem | | 12 | Linear regression and ANOVA basics |
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