SAS Online Training

SAS Platform training is a course that intends to make you an expert in the SAS programming and Analytics. After the successful completion of this course, students will be able to analyze and write SAS code to resolve technical issues, can learn tactics to use SAS datasets, learn how to import or export the manipulated data. Students will also learn methods to perform automation on complex repeated task using MACROS. They can perform the iterative and conditional looping into the SAS program and get access to the advanced statistical techniques to gain optimized results regarding the Advanced SAS programming.

Getting Started with SAS

Goal: In this module, you will learn to use the SAS Environment and program flow in SAS with specifications of Data and Proc steps. Also, you will learn to install SAS University Edition on your system.

Objective:

In this module you will learn:

• Installation of SAS University Edition 
• How to Express SAS as a language and set of rules to define SAS names
• Define the different datatypes, datasets in SAS
• Explain the significance of Data/Procedural step
• Ways to run a simple SAS program
• How to excel better controlling over Data Step Programming using PDV.

Topics:

• Use Cases of SAS implementation
• Installing SAS University Edition
• Explore SAS GUI, SAS window and its contents
• Rules for definition of a SAS name
• Different Datatypes in SAS
• Use of Formats and Informats in SAS
• Illustration of SAS Datasets
• The Data step and procedural step
• Creating an Instream SAS Dataset
• Basic Procedural statements
• Assessing Input Buffer and Program Data Vector (PDV)

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Integrating and processing with the Data Set

Goal: This module introduces you to import datasets and control the import of datasets into SAS and ultimately concatenating them.

Objective: At the end of this module, you should be able to:

• Bring in your external data into SAS and modifying it.
• Describe and subset permanent datasets.
• Modify/Delete existing columns
• Concatenate Datasets

Topics:

• Import of Data in SAS
• Manipulating influx of datasets into SAS
• Creating a new variable
• Working with Temporary and Permanent Datasets
• Set and Merge Statements

Hands On:

• Demonstrating import of external data within SAS using INFILE
• Demonstrating import of external data within SAS using PROC IMPORT
• Creating Permanent Datasets
• Performing operations with KEEP, DROP and RENAME and LABEL options
• Constructing a new variable
• Creating integrated datasets using SET/MERGE

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Ways to customize the Data Sets

Goal: This module introduces the concept of looping and its implementation in the SAS programming language. You will explore arrays and functions to simplify complications in SAS programming.

Objective: At the end of this module, you should be able to:

• Demonstrate dependent and independent looping
• Master data step programming with SAS functions
• Simplify processing with SAS Arrays

Topics:

• Conditional& Iterative Processing
• SAS Arrays
• Useful SAS Functions

Ø          PUT/INPUT Functions

Ø          Date/Time Functions

Ø          Numeric Functions

Ø          Character Functions

Hands On:

• Use of DO, DO WHILE, DO UNTIL, IF ELSE, ELSE, ELSE IF
• Demonstrate the use of arrays in SAS 
• Operation with INPUT/PUT functions
• Writing a Program with date/time functions
• Performing programming with Numeric functions
• Executing program with Character Functions

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Advanced SAS Procedures

Goal: You will learn the analysis of your statistical data with advanced SAS procedures

Objective: At the end of this module, you should be able to:

• Explain Statistical Procedures
• Define priorities to your statistical data
• Discuss statistics associated with a variable
• Express correlation between two or more variables 

Topics:

• Proc Dataset
• Proc Format
• Proc Sort
• Proc Means
• Proc Freq
• Proc Surveyselect
• Proc Transpose
• Proc Summary
• Proc Rank
• Proc Corr
• Proc Univariate

Hands On:

• Obtaining statistical means of variables
• Checking the degree of dependence within different variables
• Generating ranks for statistical data
• Performing re-structuring of data
• Conducting sampling: Random and Stratified

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Advanced Statiscal Proficiency with SAS

Goal: You will learn the analysis of your statistical data with advanced SAS procedures

Objective: At the end of this module, you should be able to:

• Explain Statistical Procedures
• Define priorities to your statistical data
• Discuss statistics associated with a variable
• Express correlation between two or more variables 

Topics:

• Proc Dataset
• Proc Format
• Proc Sort
• Proc Means
• Proc Freq
• Proc Surveyselect
• Proc Transpose
• Proc Summary
• Proc Rank
• Proc Corr
• Proc Univariate

Hands On:

• Obtaining statistical means of variables
• Checking the degree of dependence within different variables
• Generating ranks for statistical data
• Performing re-structuring of data
• Conducting sampling: Random and Stratified

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Optimization of SAS ODs and Variables

Goal: You will learn to reduce the degree of complexity of a problem by developing& resolving optimization models and ultimately routing detailed presentation output from SAS in desired formats and destination. 

Objective: At the end of this module, you should be able to:

• Discuss data optimization
• Acquire optimized models for complex problems
• Resolve optimization models
• Describe the Output Delivery System in SAS
• Explain the use of ODS statement for creation of different file types

Topics:

• What is Data Optimization?
• Realizing Optimization Models
• Using Proc Optmodel
• Solving the Rosenbrock Problem
• Introduction to ODS
• Benefits of using ODS
• Generating rtf file
• Generating pdf file
• Generating html file
• Generating doc file

Hands On:

• Writing a program with PROC OPTMODEL
• Solving the optimization model using SOLVE
• Extracting optimized outputs 
• Routing quality presentation files
• Create html files
• Create rtf file
• Create pdf and doc files

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Proc SQL

Goal: You will learn to invoke SQL in SAS.

Objective: At the end of this module, you should be able to:

• Write SQL code using various styles of the SELECT statement
• Use CASE/WHEN clauses for conditionally processing the data
• Systemize appearance of observations
• Join data from two or more data sets

Topics:

• Creating new tables
• The SELECT statement
• Sorting Data
• The CASE expression
• Other SELECT statement clauses
• JOINS and UNIONS 

Hands On:

• Demonstrating the SQL Procedure
• Writing the SELECT clause
• Application of WHERE clause
• Merging Datasets
• Using ORDER BY clause

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How to Use SAS Macros

Goal: You will explore how to automate a complex repeated process in SAS with the use of Macros.

Objective: At the end of this module, you should be able to:

• Define Macro Concept
• Automate a task that you perform repeatedly
• Explain Macro Step
• Express Macro step as a combination of different variables

Topics:

• Introduction to Macros
• Benefits of using SAS Macros
• Macro Code Constituents
• Macro Variables
• Macro Step
• Positional Parameters to Macros

Hands On:

• Demonstrate the use of Macro variables in SAS
• Writing a Macro code to simplify a program
• Demonstrate Macro step programming
• Performing Macro coding by passing parameters