Suitable for use by departments ranging from statistics and Engineering to Psychology and Education when the objective of the course is to learn to use the SAS programming language to perform statistical analysis.

As the SAS© programming language continues to evolve, this new edition follows suit with up-to-date coverage of this combination statistical package, database management system, and high-level programming language. Using examples from business, medicine, education, psychology, and other disciplines, Applied Statistics and the SAS Programming Language is an invaluable resource for both students and applied researchers, giving them the capacity to perform statistical analyses with SAS without wading through pages of technical documentation.

Features

• � Comprehensive coverage of key SAS elements - Includes the necessary SAS statements to run programs for most of the commonly used statistics, explanations of the computer output, interpretations of results, and examples of how to construct tables and write up results for reports and journal articles.
• � Logical, easy-to-follow examples - Provide readers with ample models for developing programming skills and learning to write their own programs.
• � Highly respected authorship - Lead author Ron Cody, a longtime professor and researcher at the Robert Wood Johnson Medical School, now acts as a private consultant and serves as a national instructor for the SAS Institute. He has authored or coauthored numerous books such as SAS Functions by Example, Cody's Data Cleaning Techniques Using SAS Software, The SAS Workbook, and The SAS Workbook: Solutions.

New To This Edition

• NEW -- SAS Version 9 -- The entire text is entirely up-to-date with SAS Version 9
• NEW -- SAS Graph - The text features the use of SAS Graph to replace older non-graphics procedures
• NEW -- Doubled the Number of Problems -- featuring half with answers in text and half with answers available to the instructor on the Prentice Hall website
• NEW -- Expanded Chapter on Longitudinal Data - featuring new sections on Working with two-digit year values (The Y2K Problem), Computing differences between observations in a longitudinal data set, Computing the differences between the first and last observation for each subject, Creating summary data sets with PROC MEANS or PROC SUMMARY, Outputting statistics other than means
• NEW -- Expanded Chapter on Multiple Regressions -- featuring new sections using the variance inflation factor to look for multicollinearity and Automatic creation of dummy variables with PROC LOGISTIC
• NEW -- Expanded Chapter on Character Functions -- featuring the new SAS
• Version 9 Function