Statistics Tutorials
using SAS Software
These SAS statistics tutorials briefly explain the use and interpretation of standard statistical analysis techniques for Medical, Pharmaceutical, Clinical Trials, Marketing or Scientific Research. The examples include how-to instructions for SAS Software.Although there are millions of SAS users around the world, there is a substantial learning curve involved in mastering the program.These tutorials are an introduction to using SAS statistical software that could be used in an applied statistics course or as your own self-paced tutorial. They were developed from fifteen years of teaching introductory SAS courses and include step-by-step examples of how to analyze, interpret and report the results of commonly taught statistical procedures.
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See www.stattutorials.com/SASDATA for files mentioned in these tutorials, © TexaSoft, 2007-10. All rights reserved.
Index to SAS Statistics Tutorials
- PROC MEANS Tutorial (Descriptive statistics)
- PROC MEANS OUTPUT Tutorial
- PROC UNIVARIATE Tutorial (Distribution analysis)
- New: PROC UNIVARIATE - Advanced Tutorial
- PROC CORR Tutorial (Correlation)
- PROC FREQ Tutorial 1 (Frequency Tables/Goodness of Fit)
- PROC FREQ Tutorial 2 (Two-way tables)
- PROC TTEST Tutorial (Two sample and paired t-tests)
- New: A comparison of Paired & Independent Sample t-tests
- PROC ANOVA & GLM Tutorial (One-Way ANOVA)
- PROC GLM Tutorial (Repeated measures ANOVA using PROC GLM)
- New: Survival Analysis & comparison of groups using PROC LIFEREG
- Bland-Altman Analysis (Comparing two measures)
- Inter-Rater Reliability, Kappa, Weighted Kappa (PROC FREQ)
- SAS Functions (2-part tutorial)
New: SAS Graphs Examples- New - Mantel-Haenszel analysis (pooling 2x2 tables/Meta analysis)
Special SAS Topics
- New: Read and Write SAS Data Sets the EASY way
- Setting the SAS Initial Folder (default directory)
- Using SAS ODS Output, Styles, Graphics, Data
- Examples of SAS ODS Styles New!
- Data files and SAS code for tutorials
General Statistical Tutorials
- Interpreting p-values
- Understanding hypothesis testing
- Statistical comparison of two groups
- Your comments are welcome

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