Advanced SAS Programming for R Users, Part 1
1h 44mAdvanced2018-03-22
Authors
Jordan Bakerman
Instructor, SAS Expert
Course details
SAS is one of the most used data analytics platforms in the world. Enhance your programming skillset by learning how to apply your understanding of R— the language of big data—in the SAS environment at an advanced level. Instructor Jordan Bakerman covers several different advanced techniques for analyzing data via inferential procedures. Learn about linear regression with PROC REG, estimating linear combinations with the general linear model procedure, mixed models and the MIXED procedure, and more. Note: You can visit the SAS site to obtain a copy of the software, and use the companys online data sets to do the course exercises.
Learning objectives
Analyzing the data via inferential procedures
Linear regression with PROC REG
Scoring new data sets
ANOVA and ANCOVA with the general linear model procedure
Estimating linear combinations with the general linear model procedure
Benefits of the GLMSELECT procedure
Mixed models and the MIXED procedure
Learning objectives
Analyzing the data via inferential procedures
Linear regression with PROC REG
Scoring new data sets
ANOVA and ANCOVA with the general linear model procedure
Estimating linear combinations with the general linear model procedure
Benefits of the GLMSELECT procedure
Mixed models and the MIXED procedure
Skills covered
SASStatisticsPersonaProgramming LanguagesData ScienceSoftware Development
Concepts
0. Introduction
- 01 - Welcome
1. Analyzing the Data via Inferential Procedures
- 02 - Linear regression with PROC REG
- 03 - Scoring new data sets
- 04 - Demo - Multiple linear regression
- 05 - Demo - Polynomial regression
- 06 - ANOVA and ANCOVA with the general linear model procedure
- 07 - Estimating linear combinations with the general linear model procedure
- 08 - Demo - Two-way ANOVA
- 09 - Demo - ANCOVA
- 10 - Affect selection with the GLMSELECT procedure
- 11 - Additional benefits of the GLMSELECT procedure
- 12 - Demo - Stepwise selection with PROC GLMSELECT
- 13 - Demo - Polynomial regression with the GLMSELECT procedure
- 14 - Logistic regression with the LOGISTIC procedure
- 15 - Counting concordant, discordant, and tied pairs in the logistic procedure
- 16 - Demo - Logistic regression
- 17 - Other generalized linear models with the GENMOD procedure
- 18 - Demo - GENMOD procedure
- 19 - Mixed models and the MIXED procedure
- 20 - Demo - Two-way mixed model
- 21 - Other procedures
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