Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design.
Examples and exercises contain real data and graphical illustration for ease of interpretation
Outputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but...
Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understandi...
Features and capabilities of the REG, ANOVA, and GLM procedures are included in this introduction to analysing linear models with the SAS System. This guide shows how to apply the appropriate procedure to data analysis problems and understand PROC GLM output. Other helpful guidelines and discussions cover the following significant areas: Multivariate linear models; lack-of-fit analysis; covariance and heterogeneity of slopes; a classification with both crossed and nested effects; and analysis of variance for balanced data. This fourth edition includes updated examples, new software-related...
Features and capabilities of the REG, ANOVA, and GLM procedures are included in this introduction to analysing linear models with the SAS System. This...
