HDS 5303 Statistical Inference
Statistical inference is the process of drawing conclusions about populations from data. The course provides an overview of inferential methods needed for data science research. The course emphasizes topics without overt reliance on measure-theoretic concepts. Topics include classic probability theory and statistical methods; properties of probability distributions; sampling distributions; law of large numbers; central limit theorem; asymptotic distribution theory; point estimation including unbiased estimators, sufficiency, method of moments, method of maximum likelihood, Bayesian estimation; confidence intervals for means, differences of means, proportions, differences of proportions, variances, and ratios of variances; hypothesis testing including Neyman-Pearson lemma, power function, and likelihood ratio test.