Probability Distributions:
Standard distributions such as normal, binomial, hypergeometric, Poisson,
gamma, multinomial, multivariate normal; sampling distributions of
statistics, t, F, chi-squared, order statistics; basic limit theorems such as
law of large numbers and central limit theorem
Basic Statistical Inference:
Tests of hypotheses in one-parameter probability models; standard methods of
point and interval estimation for one-parameter probability models.
Analysis of Variance:
One-factor & Two-factor Analysis of Variance models: hypothesis testing
(t-test) and F-test); multiple comparisons by Bonferroni's method; estimation
and hypothesis testing of linear contrasts.
Linear Regression Analysis:
Linear regression models; ordinary and weighted least squares; simple and
multiple regressions; inferences in regression analysis (t-test, F-test,
confidence and prediction intervals); residuals analysis; F-test for lack of
fit; coefficient of determination; partial correlations; Gauss-Markov theorem;
tests for normality.
Nonparametric Methods:
Wilcoxon-Mann-Whitney tests (both one and two sample problems); Empirical
distributions; goodness-of-fit tests; categorical data analysis; chi-squared
tests; Kolmogorov and Kolmogorov-Smirnov statistics.
Most of the material above can be found in