Department: 
Course Number: 
145
CCN: 
75622
Instructor: 
Lahiff
Units: 
4
Description: 
Regression models for continuous outcome data: least squares estimates and their properties, interpreting coefficients, prediction, comparing models, checking model assumptions, transformations, outliers, and influential points. Categorical explanatory variables: interaction and analysis of covariance, correlation and partial correlation. Appropriate graphical methods and statistical computing. Analysis of variance for one- and two-factor models: F tests, assumption checking, multiple comparisons. Random effects models and variance components. Introduction to repeated measures models.
Semester: 
Spring 2013
Term (SP for Spring; FL for Fall): 
SP