SAS Analytics


Why this course ?

  • Learn how to generate descriptive statistics and explore data with graphs and perform linear regression and assess the assumptions
  • Learn how to use diagnostic statistics to identify potential outliers in multiple regression and fit a multiple logistic regression model
  • Modify data for better analysis results, build and understand predictive models such as regression models and compare and explain complex models generate and use score code

This course covers a range of introductory statistical topics and uses SAS software to carry out analysis. Emphasis placed on the interpretation of the results. It covers the skills required to assemble analysis flow diagrams using the rich tool set and predictive modeling. Ready-to-use procedures handle a wide range of statistical techniques.

Program Duration
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Introduction to Business Analytics
Categories of Business Analytics
Installation of SAS
Importing CSV file in SAS
Concept of Linear Regression
Assumptions of Classical Linear Regression Model
Concept of Multi Collinearinty and Auto Correlation
Case study discussion and Dataset descriptions
Linear Regression Practical Session - Part - 1
Linear Regression Practical Session - Part - 2
Linear Regression Practical Session - Part - 3
Linear Regression Practical Session - Part - 4
Linear Regression Practical Session - Part - 5
Logistic Regression
Assumptions of Logistic Regression
Concept of Concordant, Discordant and Tied Pairs
Setting the probability level
Detail description of Confusion Matrix
Logistic Regression Practical part- 1
Logistic Regression Practical part- 2
Logistic Regression Practical part- 3
Logistic Regression Practical part- 4
Logistic Regression Practical part- 5
Concept of time series
Components of Time Series
Smoothing Techniques
Stationarity and non-stationarity of Time Series Data
ARIMA Modelling
BOX JENKINS Technology
Case Study and Data set discussion of Time Series
Time Series Practical Session Part- 1
Time Series Practical Session Part- 2
Time Series Practical Session Part- 3




Course Name: SAS Analytics