This course covers fundamental to intermediate regression analysis. The course builds on the ideas of hypothesis testing learned in STAT201 (Statistics I). The focus is on learning new statistical skills and concepts for real-world applications. Students will use statistical software to do the analyses. Topics include simple and bivariate linear regression, residual analysis, multiple linear model building, logistic regression, the general linear model, analysis of covariance, and analysis of time series data.
Note: Students whose prerequisites are not identified by the system should contact the Math and Statistics Department for an override at MATH@metrostate.edu.
- Communicate understanding of analysis results through clearly written conclusions summarizing the results of the statistical models when applied to specified data sets.
- Demonstrate the ability to appropriately select among different regression models for hypothesis testing, including data production design, in the context of answering questions about representative real-world problems.
- Understand and learn to interpret a more advanced set of statistical models and hypothesis testing techniques (than covered in STAT 201) such as simple and multiple linear regression models, residual analysis, and time series analysis.
- Understand statistical principles and methods for regression analysis.