PS 600

The general linear model is presented as a tool for the analysis of experimental and survey data. Topics include analysis of the general linear model (simple and multiple regression examples) by least squares, estimates of error, residual and regression sum of squares, analysis of variance for the general linear model, the concept of extra sum of squares, confidence intervals and tests of significance. An integral part of the course is the use of statistical computing packages (e.g.,R). This course consists of 3 lecture hours and 1 lab hour per week.