SAS ANALYTICS

Advanced Statistics/ Analytics

Duration: 40 Hrs

All the techniques we will show it in SAS

Introduction to Statistics

Descriptive Statistics

Measure of central Tendency Measure of Dispersion

Measure of Shape

Sampling Methods

Simple Random Sampling

Systematic Random sampling

Stratified Random sampling

Cluster Random Sampling

Non Random samplings: Quota, Judgment, Convince and Snow ball sampling

Parametric tests

One sample  test

Independent of two sample tests ( t test & Z tests) Paired t test

One Way ANOVA

Two ways ANOVA

Non parametric Tests

Mann Whitney U test

Kruskal Wallis Anova, Friedman Anova

McNemar test

Median test

Predictive Modelling technique

Simple Linear Regression (SLR)

  • OLS method
  • MLE
  • Assumption of OLS
  • Checking Assumption of SLR
  • Problem of Homoscatasity
  • Problem of Autocorrelation
  • Problem of Multicolinarity
  • Data Transformation

Multiple Linear regressions

Logistic Regression for Classification and Prediction

Forecasting Technique

ARIMA Modeling

Exponential Smoothing

Index

Multivariate Techniques

  • Factor Analysis For Data Reduction
  • Principle Component Analysis
  • Cluster Analysis for Market segmentation
  •  Discriminate Analysis for classification and Prediction
  • Multidimensional Scaling for Brand Positioning
  • Conjoint analysis for Product design
  • Canonical correlation