SAS PREDICTIVE MODELLING

SAS PREDICTIVE MODELLING TRAINING

 

SAS PREDICTIVE MODELLING TRAINING Course Content:

I. Descriptive Statistics

Introduction to Statistics

  • Measure of central Tendency
  • Measure of Dispersion
  • Measure of Shape

 

Data Preparation

  • Data Handling and preparation
  • Missing value analysis and imputation
  • Outlier identification and how handle the outlier problem

 

Sampling Methods

  • Simple Random Sampling
  • Systematic Random sampling
  • Stratified Random sampling
  • Cluster Random Sampling
  • Non Random samplings: Quota, Judgment, Convince and Snow ball sampling

II Statistical Inference

Parametric tests

  • One sample t test
  • Independent of two sample tests ( t test & Z tests)
  • Paired t test
  • One Way ANOVA
  • Two ways ANOVA

Non parametric Tests

  • Chi square Test

III. Predictive Modeling 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

IV. Multiple Linear regressions

V.  Logistic Regression for Classification and Prediction

VI. Forecasting Technique (Time series Analysis)

  • Trend analysis
  • Smoothening technique (Moving Average and Exponential smoothing
  • Auto regression
  • ARIMA Modeling
  • Exponential Smoothing

 

VII. Multivariate Techniques

  • Factor Analysis for Data Reduction
  • Cluster Analysis for Market segmentation
  • CHIAD (Decision tree)
  • CART

(Note: There will be assignment for each chapter and we observe the performance & understand you and based on this we will deliver the class.)

(Note: the practical session for these concepts will be thought through SAS Miner)

 

SAS PREDICTIVE MODELLING TRAINING duration: 80 hrs

SAS PREDICTIVE MODELLING Training demo