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