SAS Programming for Beginners : Validate Model Assumptions

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

Requirements
No sas programming experience you will learn everything
Enjoying statistics interpretations

Description
** 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.

Click the "Buy Now" to start your sas journey today.

Who this course is for
Beginner SAS programmers
SAS programmers who want to learn output interpretation
Everyone who is willing to learn how to code SAS

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