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

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

A more advanced treatment of ANOVA and regression occurs in the Statistics 2: ANOVA and Regression course. A more advanced treatment of logistic regression occurs in the Categorical Data Analysis Using Logistic Regression course and the Predictive Modeling Using Logistic Regression course.

Learn how to

• generate descriptive statistics and explore data with graphs
• perform analysis of variance and apply multiple comparison techniques
• perform linear regression and assess the assumptions
• use regression model selection techniques to aid in the choice of predictor variables in multiple regression
• use diagnostic statistics to assess statistical assumptions and identify potential outliers in multiple regression
• use chi-square statistics to detect associations among categorical variables
• fit a multiple logistic regression model
• score new data using developed models.

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