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205 – Data Analytics with SAS

This course aims to teach and develop skills for manipulating, processing, cleaning and processing data; statistical and data mining modeling with the SAS System.

Course Coverage

Data Collection, Sampling, and Preprocessing

  • Introduction to SAS
  • Types of Data Sources
  • Sampling
  • Missing Values
  • Outlier Detection and Treatment
  • Categorization
  • Weights of Evidence Coding
  • Information Value

Accessing and Assaying Prepared Data

  • Creating a SAS Project, Library, and Diagram
  • Defining and Exploring a Data Source

Predictive Modeling Fundamentals and Decision Trees

  • Introduction
  • Cultivating Decision Trees
  • Optimizing The Complexity of Decision Trees
  • Understanding Additional Diagnostic Tools
  • Autonomous Tree Growth Options

Regressions

  • Selecting Regression Inputs
  • Optimizing Regression Complexity
  • Interpreting Regression Models
  • Transforming Inputs
  • Categorical Inputs
  • Polynomial Regressions

Model Assessment

  • Model Fit Statistics
  • Statistical Graphics
  • Adjusting for Separate Sampling
  • Profit Matrices

Model Implementation

  • Internally Scored Data Sets
  • Score Code Modules

Pattern Discovery

  • Cluster Analysis
  • Basket Analysis

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Duration
3 Days