Applied Statistics

Catalog description

The purpose of this course is to teach how mathematical reasoning and statistical methods are used to analyze qualitative and quantitative data. Topics include estimation and hypotheses testing, linear and nonlinear models, generalized linear models, analysis of categorical data, elements of survival analysis and nonparametric statistical methods. Extensive use of statistical software is required. Typically offered Fall Spring. Course Learning Outcomes 1. Estimate the parameters and fit an appropriate linear regression model for a given data set. 2. Use different model checking criteria and model selection criteria to determine the best model. 3. Effectively use the regression analysis and forecasting tools. 4. Perform one way and two way ANOVA and explore factorial design. 5. Analyze the categorical data using appropriate methods. 6. Derive the elements of survival/reliability analysis. 7. Characterize, compare, and contrast different nonparametric methods. View Class Schedule