A data-driven introduction to statistics. Basic descriptive statistics, introduction to probability theory, random variables, various discrete and...
A data-driven approach to statistical modeling. Basics of experimental design, analysis of variance, simple linear regression and correlation,...
Estimation and hypothesis testing for one and two samples, analysis of categorical data, basics of experimental design, analysis of variance, simple...
Basic probability; discrete random variables with focus on binomial and Poisson random variables; continuous random variables, transformation theorem,...
Introduction to statistical computing; probability concepts; descriptive statistics; estimation and testing of hypotheses. Emphasis on the development...
Topics include: experimental design, multiple regression and correlation analysis, covariance analysis, and introductory time series. Use of computer...
Axioms of probability, basic combinatorial analysis, conditional probability and independence, discrete and continuous random variables, joint and...
Axioms of probability; conditional probability and independence; random variables; distributions: binomial, Poisson, hypergeometric, normal, gamma;...
Review of simple and multiple regression with matrices, Gauss-Markov theorem, polynomial regression, indicator variables, residual analysis, weighted...
Single and multifactor analysis of variance, orthogonal contrasts and multiple comparisons, analysis of covariance; nested, crossed and repeated...
Conditional probability and conditional expectation; Stochastic modeling; discrete time Markov chains including classification of states, stationary...
The sample survey as a vehicle for information collection in government, business, scientific and social agencies. Topics include: planning a survey,...
Discrete and continuous distributions, moment-generating functions, marginal and conditional distributions, transformation theory, limiting...
Point and interval estimation, sufficient statistics, hypothesis testing, chi-square tests with enumeration data. Precludes additional credit for STAT...
Linear regression - theory, methods and application(s). Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model...
Random variables and moment-generating functions, concepts of conditioning and correlation; laws of large numbers, central limit theorem; multivariate...
Empirical distribution functions, Monte Carlo methods, elements of decision theory, point estimation, interval estimation, tests of hypotheses,...
Probability models and basic concepts; independence and conditional probabilities; discrete, continuous and multiple random variables; distribution...
Preliminaries on probability theory; exact and asymptotic sampling distributions; unbiasedness, consistency, efficiency, sufficiency and completeness;...
Introduction to probability, characteristic functions, probability distributions, limit theorems. Prerequisite(s): STAT 3506 and STAT 3558 or...
