Linear models

• Applied Regression Analysis for MS Students by Prof. Weisberg (U Mn, Stat 5161, Fall 1994) Assignments (html and pdf)
• Prof. Weisberg, Statistics 5161: by Prof. Weisberg, Masters' level Regression Analysis (html handouts, homework assignments, datasets)
• Stat 423 by Prof. Charles Kooperberg, Applied Regression and Analysis of Variance (S+) Labs and midterm. - Winter 1996
• Course notes on Regression and Anova in S+, Generalized Linear Models by Prof. Faraway.
• Virtual Statistics 153A.Statistics 153A is an introduction to regression analysis and its applications; topics include simple regression, multiple regression, and analysis of variance (ANOVA).
• Correlation and Regression by Michael T. Brannick This course is an introduction to correlation and regression. It covers both application and theory underlying these methods, including assumptions, interpretation, limitations, and the proper use of correlation and regression techniques.
• CRDSA OJOC 560 Course Materials by Robert Wolfe Professor of Biostatistics Department of Biostatistics School of Public Health University of Michigan
• EDPSY 507 by Prof. Hale, Multivariate Prosedures in Educational Researrch (3)
  This course teaches multiple regression analysis, multiple and canonical correlation, multiple discriminant analysis, classification procedures, factor analysis. (html text)
• STATISTICS 350 Linear Models in Applied Statistics II. by Richard Lockhart, Handouts, assignments.
• Statistics 322by Robert McCulloch
• Statistics/Biostatistics 572 (1996) by Ardian Raftery, - Advanced Applied Statistics and Linear Models III - Spring Quarter, 1996
  (homeworks, datasets and comments)
• Sociology 110C by Robert A. Hanneman, Slide-Show Index
  This page is the starting point for using a series of on-line slide shows that support lectures in Sociology 110C (Introduction to Multivariate Analysis).
• Phil Pollett MS213: Introductory Data Analysis Introduction: Our objective is to introduce the basic concepts of data analysis. We shall look at the following topics in some detail: methods of summarizing and displaying data, regression and regression diagnostics, analysis of variance, introductory experimental design, chi-square tests and non-parametric methods.
  (html handouts, Assignments)
• Linear Regression a lesson by Amar Patel.
  This is a lesson which will allow students to explore notions of relationship between two variables. There are many problems and activities included in this lesson to aid learning and classroom discussion.
• Prediction Methods in Science and Technology by Agnar Höskuldsson Technical University of Denmark This website contains different material on Prediction Methods in Science and Technology.
• The Generalized Linear Models Page
• Regression Modeling Strategies With Applications to Linear Models, Logistic Regression, and Survival Analysis, by Ph.D., Professor Frank Harrell, University of Virginia School of Medicine.