Applied Statistics

Catalog description

This class focuses on how mathematical reasoning and statistical methods are used to analyze qualitative and quantitative data. Topics include estimation and hypothesis testing, linear and nonlinear models, generalized linear models, analysis of categorical data, elements of survival analysis and nonparametric statistical methods. Typically offered Fall Spring Summer. Prerequisite(s): MA 26500 FOR LEVEL UG WITH MIN. GRADE OF C- AND STAT 40001 FOR LEVEL UG WITH MIN. GRADE OF C- Course Learning Outcomes 1. Estimate the parameters and fit simple and multiple regression models. 2. Become familiar with several model checking and model selection criteria. 3. Fit a logistic regression model and Poisson regression model. 4. Perform one-way and two-way analysis of variance. 5. Analyze the categorical data. 6. Become familiar with the elements of survival analysis and nonparametric statistical methods. View Class Schedule