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.
Lernen Sie, wie Sie / 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.
Zielgruppe / Who should attend
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.
In diesem Kurs wird mit folgenden Software Modulen gearbeitet / This course addresses SAS/STAT Software
This course also addresses Base SAS software and touches on SAS/GRAPH software. You can benefit from this course even if SAS/GRAPH software is not installed at your location.