Binomial, Poisson, discrete uniform, hypergeometric, normal, standard normal, t, chi-square, F, and uniform. Know their properties, graphs, tables, and applications. Know the relationships between them.
Sample space, probability density function, probability mass function, cumulative distribution function, mean, variance, standard deviation, coefficient of variation, continuity correction, degrees of freedom, skewness.
Retrospective (case-control), prospective (cohort), cross-sectional (observational).
Prevalence, incidence, sensitivity, specificity, predictive value positive, predictive value negative, false positive, false negative, odds, odds ratio, log odds ratio, relative risk, Bayes' theorem.
Histogram, fuzzygram, frequency polygon, stem-leaf plot, dot diagram, box plot, grouped box plot, scatter plot, SPLOM, coded data, sample median, sample mean, sample variance, sample standard deviation, exploratory data analysis (EDA).
Univariate, bivariate, multivariate, covariance, correlation, (Pearson's) correlation coefficient, autocorrelation, independence, time series, lagged scatterplot.
Sampling distribution, standard error, point estimate, unbiased estimate, confidence interval, delta-method, test of hypothesis, (null) hypothesis, alternative (hypothesis), simple hypothesis, composite hypothesis, one-tailed test, two-tailed test, statistically significant, level of significance, alpha, beta, test statistic, reference distribution, critical value, rejection region, type I error, type II error, power, power curve, operating characteristic, p-value, mid-p, robustness.
One-way (one-factor) ANOVA, two-way (two-factor) ANOVA, grand mean, factor, main effect, interaction, sum of squares, mean square, F-ratio, degrees of freedom, residual, regression, regression coefficients, regression line, intercept, slope, conditional variance, pure error.
Contingency table, independence, homogeneity, sign test, Wilcoxon signed-rank test.