This course is for experienced R users who want to apply their existing skills and extend them to the SAS environment. Emphasis is placed on programming and not statistical theory or interpretation. Students in this course should have knowledge of plotting, manipulating data, iterative processing, creating functions, applying functions, linear models, generalized linear models, mixed models, stepwise model selection, matrix algebra, and statistical simulations.

Learn How To

read and write SAS programsimport various forms of datasubset and merge data tables do iterative processing and simulate new datacreate new variables and functionscreate and enhance plots of all typesapply descriptive and inferential procedures including regression, logistic regression, analysis of variance, stepwise model selection, and mixed modelsconduct matrix algebra and statistical simulations in the interactive matrix language (IML)call R from SAS to use as a complementary resource.Who Should Attend

Experienced R users who want to augment their programming skills with SAS

Prerequisites

Students should have knowledge of plotting, manipulating data, iterative processing, and creating and applying functions. They should also have knowledge of linear models, generalized linear models, mixed models, stepwise model selection, matrix algebra, and statistical simulations.

SAS Products Covered

Base SAS;SAS/STAT;SAS/IML

Course Outline

Introduction

introduction SAS programming (self-study) accessing data in SAS librariesImporting and Reporting Datathe DATA step and manual data entry importing data reporting the data enhanced reporting Creating New Variables, Functions, and Data Tablescreating new variables creating and using functions subsetting and concatenating data tablesRandom Number Generation and PlottingDO loop and random number generation single-cell plotting multi-cell plottingDescriptive Procedures, Output Delivery System, and MacrosCORR, FREQ, MEANS, and UNIVARIATE procedures Output Delivery System (ODS) creating macro variables creating macro programsAnalyzing the Data via Inferential Procedureslinear models generalized linear models mixed models other proceduresInteractive Matrix Language (IML)the basics (self-study)modules and subroutines calling SAS data sets and procedures simulationsA Bridge between SAS and Rcalling R from IML calling R from Base SAS Java API (self-study) calling R from SAS Enterprise Miner (self-study)