Statistical Data Analysis Using SAS

This book is an integrated treatment of applied statistical methods, presented at an intermediate level. It serves as an advanced introduction to the SAS programming language as well as demonstrating how to use SAS to analyse of a wide variety of data.

Integrates SAS programming with complex data analysis applications
Focuses on using SAS and statistical aspects of models and methods of analysis
Introduction to SAS - beyond the basics and illustrated with numerous worked examples
Advanced material suitable for a second course in applied statistics with every method explained using a SAS analysis to illustrate a real-world problem
15-20 problems in every chapter
End of chapter exercises
Solutions to exercises
Downloadable SAS code and data sets

Integrates SAS programming with complex data analysis applications Focuses on using SAS and statistical aspects of models and methods of analysis Introduction to SAS - beyond the basics and illustrated with numerous worked examples Advanced material suitable for a second course in applied statistics with every method explained using a SAS analysis to illustrate a real-world problem 15-20 problems in every chapter End of chapter exercises Solutions to exercises Downloadable SAS code and data sets

Autorentext
Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. He has taught a data analysis course based on SAS for over 35 years and offered workshops and short-courses on various aspects of SAS including traditional SAS programming, SAS Enterprise Guide, SAS Enterprise Miner, and JMP for many years to both university audiences and non-academic participants.

Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.

Inhalt
1 Introduction to the SAS Language.- 2 More on SAS Programming and Some Applications.- 3 Introduction to SAS Graphics.- 4 Statistical Analysis of Regression Models.- 5 Analysis of Variance Models.- 6 Analysis of Variance: Random and Mixed Effects Models.- 7 Beyond Regression and Analysis of Variance.- Appendices.- References.