Getting Started with SAS/STAT
Learn all about SAS/STAT and get started with SAS/STAT today.
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Want to make it through the next interview you will appear for? Hone your skills with our two-part series of interview questions widely asked in the industry. With basic to advanced questions, this is a great way to expand your repertoire and boost your confidence.
Wipe the slate clean and learn SAS/STAT from scratch
Introduction to SAS/STAT
Features of SAS/STAT
Pros and Cons of SAS/STAT
SAS/STAT Bayesian Analysis Procedures
SAS/STAT ANOVA (Analysis of Variance)
Categorical Analysis in SAS/STAT
Cluster Analysis in SAS/STAT
SAS/STAT Group Sequential Design & Analysis
SAS/STAT Longitudinal Data Analysis Procedures
SAS/STAT Mixed Model Procedures
Market Research in SAS/STAT
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SAS/STAT Model Selection
SAS/STAT Descriptive Statistics Procedures
SAS/STAT Distribution Analysis
SAS/STAT Missing Data Analysis Procedures
SAS/STAT Multivariate Analysis
SAS/STAT Non Linear Regression
Exact Inference in SAS/STAT
SAS/STAT Discriminant Analysis
SAS/STAT Post Processing Procedures
SAS/STAT Power and Sample Size Analysis
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SAS/STAT Non-Parametric Regression
Quantile Regression in SAS/STAT
SAS/STAT Predictive Modeling Procedures
SAS/STAT Regression Analysis Procedures
SAS/STAT Robust Regression Procedures
SAS/STAT Psychometric Analysis Procedures
SAS/STAT Survival Analysis Procedures
SAS/STAT Spatial Analysis Procedures
Standardization in SAS/STAT
SAS/STAT Interview Questions- Part 1
SAS/STAT Interview Questions- Part 2
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Exploring the Software
Let’s take a look at some facts about SAS/ STAT and its philosophies.
SAS/STAT is state-of-the-art statistical analysis software. It lets us perform tasks like analysis of variance and linear regression and Bayesian inference. It delivers tools for specialized and enterprisewide statistical needs. Proven techniques produce accurate results. SAS/STAT lets us apply statistical techniques to any size of data and capitalize on technical support and web user communities. We can also rely on validated algorithms and make use of the simplicity of a single environment.
SAS Institute