Department of Statistics

Current Sections   Recent Instructors Wang, J	ST 372	Introduction to Statistical Inference and Regression
	Course Description Statistical inference and regression analysis including theory and applications. Point and interval estimation of population parameters. Hypothesis testing including use of t, chi-square and F. Simple linear regression and correlation. Introduction to multiple regression and one-way analysis of variance. Course Syllabus Random samples Linear combinations of independent random variables Sample mean Review of normal distribution, Central Limit Theorem Continuity correction Point estimation Statistic and parameter Sample variance Method of moments Maximum likelihood estimators Principle of invariance Data analysis Hypothesis testing Confidence intervals Single populations Tests on means: Normal distribution and t distribution Tests on variance: Chi-squared distribution Comparison of populations Tests on means: Smith-Satterwaite Pooled sample variance Test on variance: F-distribution Large sample approximations Chi-squared tests Goodness of fit tests Contingency tests Analysis of variance Linear regression Standard linear model Least squares model Least squares criterion Estimation of intercept and slope Course Prerequisites ST 371 Course Corequisites None Recent Textbooks Probability and Statistics for Engineering and the Sciences, 6 ed. Devore (2003)