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Comprehensive SAS Predictive Modeling : Hands-On Training

In This Course Master The Skills Required To Assemble Analysis Flow Diagrams Using The Rich Tool Set And Predictive Modeling.

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

Course Preview Video

  • Author

    Hands On

  • Categories

    Profession

  • Duration

    07:21:22

  • 0 Students Enrolled

Master Ready-To-Use Procedures To Handle A Wide Range Of Statistical Techniques.

Description

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.

Learn how to

  • generate descriptive statistics and explore data with graphs
  • perform linear regression and assess the assumptions
  • use diagnostic statistics to identify potential outliers in multiple regression
  • fit a multiple logistic regression model
  • modify data for better analysis results
  • build and understand predictive models such as regression models
  • compare and explain complex models generate and use score code
  • learn how to predict for future through time series analysis
  • learn classification techniques using cluster analysis
  • learn dimension reduction using factor analysis

Basic knowledge
  • Basic knowledge of computer is sufficient for this course

What will you learn
  • Mean Median Mode
  • Measures of variance
  • probability
  • Binomial Distribution
  • Poisson Distribution
  • normal distribution
  • Sampling distribution
  • Hypothesis Testing
  • One Sample T-Test
  • Two Sample T-Test
  • chi-square test
  • ANOVA
  • Multiple Regression
  • Logistic Regression
  • Time Series
  • ARIMA Modeling
  • Cluster Analysis
  • Factor Analysis
Course Curriculum
Number of Lectures: 55 Total Duration: 07:21:22
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