 Module1SAS ESSENTIALS

An Overview of the SAS System
Getting Started With the SAS System
Getting familiar with SAS Data Sets
Producing List Report
Enhancing Output
Creating SAS Data Sets
DATA Step Programming
Combining SAS Data Sets
Producing Summary Reports
Introduction to Graphics
 Module2SASPROGRAMMINGII

Introduction to Data Step Manipulation
Controlling Input and Output
Creating an Accumulating Variable
Reading & Writing Different Types of Data
Data Transformations
Debugging Techniques
Processing Data Iteratively
Combining SAS Data sets
Learning More
 Proc SQL and Macro

Introduction to SQL Procedure
Retrieving Data From a Single Table
Retrieving Data from Multiple Tables
Creating and Updating Tables and Views
Programming with the SQL Procedure
Practical ProblemSolving with PROC SQL
 Introduction to Analytics and Basic Statistics

Types of Analytics
Properties of Measurements
Scales of Measurement
Types of Data
Measures of Central Tendency
Measures of Dispersion
Presentation of Data
Skewness and Kurtosis
 Introduction to Probability Theory

Three Approaches towards Probability
Concept of a Random Variable
Probability Mass Function
Probability Density Function
Expectation of a Random Variable
Probability Distributions
 Sampling Theory and Estimation

Theory of Sampling
Concept of Estimation
Different types of Estimation
 Testing of Hypothesis

Concept of Hypothesis
Null Hypothesis
Alternative Hypothesis
TypeI error
TypeII error
Level of Significance
Confidence of Interval
Parametric Tests and Non Parametric Tests
One Sample T test
Two independent sample T test
Paired Sample T test
Chi Square Test for Independence of Attributes
 Sampling Theory and Estimation

Theory of Sampling
Concept of Estimation
Different types of Estimation
 Analysis of Variance

One Way Anova
Two Way Anova
 Exploratory Factor Analysis

Principal Component Analysis
Estimating the Initial Communalities
Eigen Values and Eigen Vectors
Correlation Matrix check and KMOMSA check
Factor loading Matrix
Diagrammatic Representation of Factors
Problems of Factor Loadings and Solutions
 Linear regression and Multiple Linear Regression

Concept of Regression and features of linear line.
Assumptions of Classical Linear Regression Model
Method of Least Squares
Understanding the Goodness of fit
Test of Significance of the Estimated Parameters
Multiple Linear Regression and their Assumptions
Concept of Multicollinearity
Signs of Multicollinearity
The Idea of Autocorrelation
 Cluster Analysis

Types of Clusters
Metric and Linkage
Wardâ€™s Minimum Variance Criteria
SemiPartial RSquare and RSquare
Diagrammatic Representation of clusters
Problems of Cluster Analysis
 Logistic Regression

Concept and Applications of Logistic Regression
Principles Behind Logistic Regression
Comparison between Linear Probability Model and Logistic Regression
Mathematical Concepts Related to Logistic Regression
Concordant Pairs, Discordant Pairs and Tied Pairs
Classification Table
Graphical Representation Related to Logistic Regression
 Time Series Analysis

Concept of Time Series and its Applications
Assumptions of Time Series Analysis
Components of Time Series
Smoothening Techniques
ARIMA Modelling
BoxJenkins Technology
 Basic R

Introduction to R
Basic Operations in R
Different Data Types and Data Structures In R
Subsetting In R
Additional Topics on Data Structures
Importing Data Sets in R
R Loops and Special Functions
Calculation of Commission and Simple Interest
Plots and Charts in R
Merging and Sorting Functions in R
Summarising Data
Calculations of the Measures of Central Tendency and Measures of Dispersion or Variability
 Introduction to Analytics and Basic Statistics

Types of Analytics
Properties of Measurements
Scales of Measurement
Types of Data
Measures of Central Tendency
Measures of Dispersion
Presentation of Data
Skewness and Kurtosis
 Exploratory Factor Analysis

Principal Component Analysis
Estimating the Initial Communalities
Eigen Values and Eigen Vectors
Correlation Matrix check and KMOMSA check
Factor loading Matrix
Diagrammatic Representation of Factors
Problems of Factor Loadings and Solutions
 Introduction to Probability Theory

Three Approaches towards Probability
Concept of a Random Variable
Probability Mass Function
Probability Density Function
Expectation of a Random Variable
Probability Distributions
 Sampling Theory and Estimation

Theory of Sampling
Concept of Estimation
Different types of Estimation
 Analysis of Variance

One Way Anova
Two Way Anova
 Testing of Hypothesis

Concept of Hypothesis
Null Hypothesis
Alternative Hypothesis
TypeI error
TypeII error
Level of Significance
Confidence of Interval
Parametric Tests and Non Parametric Tests
One Sample T test
Two independent sample T test
Paired Sample T test
Chi Square Test for Independence of Attributes
 Time Series Analysis

Concept of Time Series and its Applications
Assumptions of Time Series Analysis
Components of Time Series
Smoothening Techniques
ARIMA Modelling
BoxJenkins Technology
 Market Basket Analysis

Support
Lift
Confidence
 Text Mining Analysis

Decision Tree
MANOVA
 Spreadsheet Analytics using Excel and VBA

Working with Formulae and Functions
Conditional Formatting in Excel
Data Sorting and Filtering, Excel Advanced Filter Options
Pivot Tables
VBA(Visual Basic Application)