Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression

This course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t-tests, ANOVA, linear regression, and logistic regression. This course (or equivalent knowledge) is a prerequisite to many of the courses in the statistical analysis curriculum.

Certification:

  • SAS Certified Clinical Trials Programmer Using SAS 9
  • SAS Statistical Business Analysis Using SAS 9: Regression and Modeling

    No classes are currenty scheduled for this course.

    Call (919) 283-1653 to get a class scheduled online or in your area!

1. Course Overview and Review of Concepts

  • Descriptive statistics
  • Inferential statistics
  • Examining data distributions
  • Obtaining and interpreting sample statistics using the univariate procedure
  • Examining data distributions graphically in the univariate and freq procedures
  • Constructing confidence intervals
  • Performing simple tests of hypothesis
  • Performing tests of differences between two group means using PROC TTEST

2. ANOVA and Regression

  • Performing one-way ANOVA with the GLM procedure
  • Performing post-hoc multiple comparisons tests in PROC GLM
  • Producing correlations with the CORR procedure
  • Fitting a simple linear regression model with the REG procedure

3. More Complex Linear Models

  • Performing two-way ANOVA with and without interactions
  • The concepts of multiple regression

4. Model Building and Effect Selection

  • Automated model selection techniques in PROC GLMSELECT to choose from among several candidate models
  • Interpreting and comparison of selected models

5. Model Post-Fitting for Inference

  • Examining residuals
  • Investigating influential observations
  • Assessing collinearity

6. Model Building and Scoring for Prediction

  • The concepts of predictive modeling
  • The importance of data partitioning
  • The concepts of scoring
  • Obtaining predictions (scoring) for new data using PROC GLMSELECT and PROC PLM

7. Categorical Data Analysis

  • Producing frequency tables with the FREQ procedure
  • Examining tests for general and linear association using the FREQ procedure
  • Exact tests
  • The concepts of logistic regression
  • Fitting univariate and multivariate logistic regression models using the LOGISTIC procedure
  • Using automated model selection techniques in PROC LOGISTIC including interaction terms
  • Obtaining predictions (scoring) for new data using PROC PLM

*Please Note: Course Outline is subject to change without notice. Exact course outline will be provided at time of registration.

Exercises or hands-on workshops are included with most SAS courses.

Statisticians, researchers, and business analysts who use SAS programming to generate analyses using either continuous or categorical response (dependent) variables

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