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.

• 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.

Module 1: Course Overview and Review of Concepts

Module 2: ANOVA and Regression

Module 3: More Complex Linear Models

Module 4: Model Building and Effect Selection

Module 5: Model Post-Fitting for Inference

Module 6: Model Building and Scoring for Prediction

Module 7: Categorical Data Analysis

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