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.

**Aprenda como**
- 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.

#### Quem poderá participar

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

Before attending this course, you should:

- Have completed the equivalent of an undergraduate course in statistics covering
*p*-values, hypothesis testing, analysis of variance, and regression. - Be able to execute SAS programs and create SAS data sets. You can gain this experience by completing the SAS Programming 1: Essentials course.

Este curso aborda SAS/STAT software.