# SAS Programming for Data Science: Statistical Modelling

Beginners in SAS: DO Loops, IF-THEN/ELSE, IF-THEN/DO , Multicollinearity, Linearity, Normality Tests, Outlier detection

** New to SAS**

What you’ll learn

• Understand the basics of DATA Step & Procedure Step.
• Learn to define SAS variables using NUMBERED RANGE LIST.
• Learn to access EXCEL FILES & CSV FILES in SAS data using a library & IMPORT procedure.
• Learn to use RENAME, KEEP & DROP statements.
• IF-THEN/ELSE statements.
• IF-THEN/DO statements.
• DO Loops : DO WHILE & DO UNTIL.
• Validate Statistics Model Assumptions by Visualization Techniques in SAS.
• Multicollinearity or Collinearity Diagnostics.
• Validate Linearity Assumption.
• Normality Test : Shapiro Wiks Test for Normality.
• Outlier Detection & Influential Observations.
• Interpretation of Cook’s Distance plots.
• Interpretation of DFFETS & DFBETAS plots.
• WELL INTERPRETATION OF ALL THE RESULTS.

Course Content

• Course Introduction –> 1 lecture • 2min.
• SAS Studio on SAS for Academic –> 1 lecture • 1min.
• Understanding SAS Syntax –> 2 lectures • 2min.
• Defining SAS Variables –> 5 lectures • 10min.
• SAS OPERATORS –> 4 lectures • 5min.
• ACCESSING DATA IN SAS –> 7 lectures • 21min.
• CONTROL OUTPUT OF VARIABLES –> 4 lectures • 9min.
• DATA MANIPULATION –> 12 lectures • 30min.
• DATA PREPROCESSING – VALIDATING MODEL ASSUMPTIONS –> 12 lectures • 38min.

Requirements

** New to SAS**

Do you want to learn how to use SAS programming from the beginners to validating machine learning algorithms assumptions ?

Are you starting your new SAS journey?

Are you looking to know how to well interpret sas output?

If you are that person , then you are about to enroll in the best course to guide you!

Your Instructor has more than 3 years of SAS experience.

Why learn SAS?

SAS jobs !

Try to search for “SAS Jobs” online. Your search is sure to turn up many current job listings that require a variety of SAS expertise. Since, SAS emerges as a key research data analysis tool, it is in demand in the market. Every company is looking for SAS resources.

SAS is fun !

It is fun learning SAS. It provides easy way to access multiple applications. It relies on user-written scripts or “programs” that are processed when requested to know what to do. Because it is a script-based application, the key to being successful using SAS is learning the rules and tricks of writing scripts. It works with large data and generate graphs and report.

Data Analysis

SAS is versatile and powerful enough for data analysis. SAS is flexible, with a variety of input and output formats. It has numerous procedures for descriptive, inferential, and forecasting types of statistical analyses. Because the SAS System is an integrated system with similar architecture shared by modules or products, once you master one module, you can easily transfer the knowledge to other modules.

By the end of this course you will be able to :

• Use numbered range list to name SAS variables
• Understand SAS libraries & how to access data in SAS using a library
• Import unstructured data into SAS
• Use SAS operators
• Use sas IF statements
• IF – THEN/ELSE statements
• IF-THEN/DO statements
• Understand DO Loops
• Use DO WHEN & DO UNTIL statements
• Use missing() function to deal with missing values
• Use noduprecs & SORT procedure to remove duplicates
• Write a neat sas syntax and be able to interpret the sas output
• How to detect Multicollinearity or Collinearity Diagnostics
• Use Variance Inflation Factor (VIF) to detect multicollinearity
• Use Condition Index (Condition numbers) to detect Multicollinearity
• Perform and Interpret Shapiro Wiks Test Normality Test
• Validate Linearity Assumption
• Carry out Pearson Correlation Test and Interpret the results using p – values
• Carry out RESIDUAL DIAGNOSTICS test and Interpret the results
• Detect Outliers & Influential Observations
• Interpret DFFITS & DFBETAS plots

Why wait when you can learn how to well write sas programs from scratch!

Don’t miss this opportunity of continuous learning.