Select the desired Level or Schedule Type to find available classes for the course. |
STAT 51200 - Applied Regression Analysis |
Credit Hours: 3.00. Inference in simple and multiple linear regression, residual analysis, transformations, polynomial regression, model building with real data, nonlinear regression. One-way and two-way analysis of variance, multiple comparisons, fixed and random factors, analysis of covariance. Use of existing statistical computer programs. Prerequisite: Coursework in Statistical Methods with a calculus prerequisite. Typically offered Fall Spring Summer.
0.000 OR 3.000 Credit hours Syllabus Available Levels: Undergraduate, Graduate, Professional Schedule Types: Distance Learning, Individual Study, Lecture All Sections for this Course Offered By: College of Science Department: Statistics Course Attributes: Upper Division May be offered at any of the following campuses: West Lafayette Continuing Ed PU Fort Wayne IUPUI Northwest- Hammond West Lafayette Learning Outcomes: 1. Learn to build and analyze simple and multiple regression models, analysis of variance and covariance (ANOVA/ANCOVA) for regression, inference for regression, diagnostics and remedial measures for regression, transformations, residual analysis, model building, polynomial and interaction models. Restrictions: May not be enrolled as the following Classifications: Sophomore: 45 - 59 hours Sophomore: 30 - 44 hours Freshman: 0 - 14 hours Freshman: 15 - 29 hours Prerequisites: GR-STAT 51200 Requisites General Requirements: ( Student Attribute: GR May not be taken concurrently. ) or ( Course or Test: STAT 50300 Minimum Grade of C- May not be taken concurrently. ) or ( Course or Test: STAT 51100 Minimum Grade of C- May not be taken concurrently. ) or ( Course or Test: STAT 51700 Minimum Grade of C- May not be taken concurrently. ) or ( Course or Test: STAT 35000 Minimum Grade of C- May not be taken concurrently. ) or ( Course or Test: STAT 41700 Minimum Grade of C- May not be taken concurrently. ) |
Return to Previous | New Search |