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Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression
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Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression
Data Science
21 hour
Advanced
Free
Description
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.
What will you learn?
- 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
What prior knowledge do you need?
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 Programmierung 1: Grundlagen course.