These are newly developed exams and there is no history to rely on. The syllabus for SRM includes the following topics:
- Basics of Statistical Learning
- Linear Models
- Time Series Models
- Principal Components Analysis
- Decision Trees
- Cluster Analysis
A combination of Statistics and Data Science courses, such as MAT 356, MAT 358, MAT 360 as well as DSC 323, DSC 324, and DSC 341, cover these topics from both a theoretical and a practical perspective. Graduate-level courses addressing the same topics are MAT 456, MAT 512, MAT 491 or the Applied Statistics sequence MAT 441-3.
Regarding Exam PA, the skills tested– in particular:
- Model Building Process
- Problem Definition and Exploratory Data Analysis
- Model Selection
- Model Validation
- Communication of Results
– appear across the entire Statistics and Data Science curriculum.