SAS

The Statistical Analysis System (SAS) is the largest analytical software being used extensively world-wide. And this is the first choice in analytics and predictive modeling among fortune 500 companies. With its extensive data analytics capabilities and easy to remember language is now the Market Leader. In data analytics, around 40 to 50 percent works are related to data exploration, data cleaning and data manipulation, around 30 to 40% are related to analysis and 10 to 20 % belongs to Reporting. SAS in the topper in all 3 segments. SAS procedures and functions are very powerful and easy to use as well.

CARRER IN SAS

Reports say that data analytics industry is the highest paid and fastest growing industry in the world. It is growing by more than 20% every year. And demand of SAS analyst is increasing every day.

WHY TO LEARN SAS?

SAS software is the market leader in business intelligence Machine Learning and Forecasting. It is a one stop solution for data importing, Cleaning, Data Manipulation, Formatting, Analysis, Statistical Analysis, Reporting and Presentation. The SAS Institute is the world's largest privately held software company. It is the only vendor that completely integrates data warehousing, analytics and BI applications, to create intelligence from big amounts of data.

As compare to other software SAS is easy to learn and it has very simple coding with lots of Menu driven Facilities. The big advantage of learning SAS is that it is a fourth generation language. It is fun learning SAS. It provides GUI and an easy way to access multiple applications. Writing scripts. It works with large data and generates graphs and report.

COURSE CONTENTS

SAS uses in different areas mainly in Clinical, Finance, Market Research

BASE SAS

Introduction to SAS Programming Working in the SAS Environment

  • Introduction

Working with the windows

  • Program editor window
  • Log window
  • Output window
  • Result window
  • Explorer window

Overview of libraries

  • Datasets
  • Data view
  • Catalog
  • Referencing Files in SAS Libraries

Basic concepts

  • Creating a SAS Programs
  • Components of SAS Programs
  • Characteristics of SAS Programs
  • Layout of SAS Programs

Methods for getting data into SAS

Methods for getting data into SAS can be put into four general categories:

  • Entering data directly into SAS data sets
  • Creating SAS data sets from raw data files
  • Converting other software's data files into SAS data sets
  • Reading other software's data file directly

Input Styles

  • List input
  • Column input
  • Formatted input
  • Modified/Mixing input
  • Reading Messy Raw Data
  • Reading Multiple lines of Raw Data per observation
  • Reading Multiple observations per line of raw data
  • Reading delimited file with DATA step

Assigning Variable Attributes

  • Permanent Attributes
  • Temporary Variable Attributes

Pointers

  • Column pointers
  • Line Pointers

Informats and Formats

  • Informats
  • Character informats
  • Numeric informats
  • Date and time informats
  • Formats
  • Character formats
  • Numeric formats
  • Date and time formats

Functions

  • Arithmetic Functions
  • String Functions
  • Date and Time Functions

Reading Raw Data from External File

  • Infile statement
  • Import
  • Export

Options

  • Lobal options
  • Local Options

Statements

  • Global Statements
  • Local Statements

Control Statements

  • If statement and if else statement
  • If then else statement
  • Where statement
  • Loops (do, dountil, dowhile)

Procedures

  • Proc Print
  • Proc Transpose
  • Proc Sort
  • Proc Contents
  • Proc Formats
  • Proc Append
  • Proc Tabulate
  • Proc Import
  • Proc Report
  • Proc Export
  • Proc Datasets
  • Proc Freq
  • Proc Means
  • Proc Reg

ADVANCED SAS

SAS/SQL

  • Introduction to Proc SQL
  • Creating tables
  • Inserting data into tables
  • Alter the tables & etc…
  • Modifying the tables

Retrieving Data from Multiple tables

  • Natural Join
  • Inner Join
  • Outer Join (Right, Left, Full)

SAS/GRAPH

  • Introduction to Graphs
  • Types of Graphs
  • Chart
  • Plot
  • Illustration of axis options
  • Illustration of symbol options
  • Illustration of footnote, note, title

SAS/STAT

  • Introduction to Statistics
  • Producing Descriptive Statistics
  • Computing Statistics for Numeric

Variables

Procedures

  • Proc Correlation
  • Proc Regression
  • Proc Means
  • Proc Summary
  • Proc Univariate
  • Proc Freq
  • Proc Annova

Combining SAS Datasets

  • Concatenating
  • Merging
  • One-to-one merging
  • One-to-many merging
  • Many-to-one merging
  • Many-to-many merging
  • Matching merging
  • Updating

Debugging of Errors

  • Writing SAS programs that work
  • Fixing programs that Don't work
  • Searching for the Missing Semicolon

Understanding Data step Processing

  • Program data vector(PDV)
  • Compilation Phase
  • Execution Phase
  • Creating a File shortcut with the File

Shortcut Assignment Window

  • Making a file shortcut to a program
  • Deleting a file shortcut
  • Browsing and submitting a file

Shortcut for a SAS program

  • Viewing file shortcut properties
  • Deleting a file shortcut
  • Browsing and submitting a file

Output Delivery System (ODS)

  • Fundamentals of the ODS
  • ODS and the Data step
  • Syntax for ODS Enhanced features in a Data step
  • Introduction to ODS language Statements

SAS/MACROS

  • Introduction to Macro Language Elements
  • Introduction to Macro Variables
  • Automatic Macro Variables
  • User defined Macro Variables
  • Introduction to Macro Processing
  • Macro Statements
  • Macro Functions

Retrieving Data from Single Table

  • Integration of Database
  • Connecting to a DBMS Using the SQL
  • Procedure Pass-Through Facility
  • Connecting to a excel Using the SQL
  • Procedure Pass-Through Facility
  • Connecting to a access Using the SQL
  • Procedure Pass-Through Facility
  • Connecting to a DBMS Using the Libname Statement

SAS/ACCESS

  • Define SAS/Access Software
  • Identify the types of data repositories that SAS/Access can access
  • The interface engine
  • The SAS/Access Libname Statement
  • The SQL Procedure Pass-Through
  • Facility
  • The Access Procedure
  • Requirements to Connect to a Database
  • SAS/Access Libname engines
  • Data sources

ADVANCE ANALYTICS

Introduction to analytics

  • Need for analytics
  • Analytics use in different industries
  • Challenges in adoption of analytics
  • Overview of Course Contents

Data understanding

  • Data types (Nominal, Ordinal, Interval and Ratio)
  • Descriptive statistics
  • Tabular & Graphical Method
  • Summary statistics

Introduction to some statistical terminologies and inferences

  • Population, Sample and Random variables
  • Point and Interval Estimations
  • Probability
  • Discrete/Continuous Probability
  • Distributions
  • Hypothesis Testing
  • Importance of formulating and validating the hypothesis
  • Formulation of hypothesis (Null and alternate)
  • Testing association and differences
  • Statistical significance and test statistic
  • Level of significance

Z-Test, T-Test, Chi-Square test, ANOVA

Correlation & Regression

Linear Regression

  • Case Study on Multiple Regression

Logistic Regression

  • Case Study on Logistic Regression

Cluster Analysis

  • Case Study on Cluster Analysis Factor Analysis

Case Study on Factor Analysis