Statistical Decisions Using ANOVA and Regression Course
This course teaches you how to use analysis of variance and regression methods to analyze data with a single continuous response variable and introduces statistical model building.
You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals and hypothesis testing are introduced and applied. The course also covers principles of model building, including model interpretation and addressing violations of statistical assumptions. Capstone practices at the end of the course allow students to apply their knowledge.
Learn how to:
- Interpret confidence intervals.
- Perform hypothesis tests and interpret p-values.
- Explore relationships with scatterplots and correlation statistics.
- Compare multiple population means with one-way ANOVA.
- Use simple linear regression to analyze relationships between continuous variables.
- Use the general linear model to build models between a continuous response and any number of continuous or categorical predictors.
- Assess interactions between factors and curvature.
- Evaluate assumptions of statistical hypothesis testing.