SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression (Free e-learning course)

This course is designed for SAS Enterprise Guide users who want to perform statistical analyses.

Duration 3 Days
Certificate SAS Global
Language English

Fees 2100


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About Program

This course is designed for SAS Enterprise Guide users who want to perform statistical analyses. The course is written for SAS Enterprise Guide 7.1 along with SAS 9.4, but students with previous SAS Enterprise Guide versions will also get value from this course. An e-course is also available for SAS Enterprise Guide 5.1 and SAS Enterprise Guide 4.3.

Format of Training

Taught by certified instructors at high-tech facilities across the country

All the benefits of the classroom without the travel

  • Join the classroom right from your desktop
  • Led by an expert instructor who can virtually look over your shoulder
  • Ask questions and get answers in real-time
  • Access the latest software via a virtual lab
  • Receive 20 business days' access to a recording of your course
  • Discuss, share, exchange ideas with participants from different countries

Training Features

 

  • generate descriptive statistics and explore data with graphs
  • perform analysis of variance
  • perform linear regression and assess the assumptions
  • use diagnostic statistics to identify potential outliers in multiple regression
  • use chi-square statistics to detect associations among categorical variables
  • fit a multiple logistic regression model.

Course Curriculum

Prerequisite Basic Concepts

 

  • discussing descriptive statistics
  • discussing inferential statistics
  • listing steps for conducting a hypothesis test
  • discussing basics of using your SAS software

Getting Started in Enterprise Guide 7.1

 

  • introducing to the SAS Enterprise Guide 7.1 environment

Introduction to Statistics

 

  • discussing fundamental statistical concepts
  • examining distributions
  • describing categorical data
  • constructing confidence intervals
  • performing simple tests of hypothesis

Analysis of Variance (ANOVA)

 

  • performing one-way ANOVA
  • performing multiple comparisons
  • performing two-way ANOVA with and without interactions

Regression

 

  • using exploratory data analysis
  • producing correlations
  • fitting a simple linear regression model
  • understanding the concepts of multiple regression
  • building and interpreting models
  • describing all regression techniques
  • exploring stepwise selection techniques

Regression Diagnostics

 

  • examining residuals
  • investigating influential observations and collinearity

Categorical Data Analysis

  • describing categorical data
  • examining tests for general and linear association
  • understanding the concepts of logistic regression and multiple logistic regression
  • performing backward elimination with logistic regression

Course Fees

Classroom

  

  

2100

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