MATH 3180: Predictive Analytics
University of North Carolina, Charlotte
Predictive modeling skills used in pricing and risk classification algorithms in the R programming language.� Students learn how to perform�exploratory data analysis using the data visualization tools in Base R and the GGPlot graphical l package. Students will learn how to apply Generalized Linear Modeling (GLM) techniques based on Gaussian, Binomial, Poisson, and Gamma families of distributions.� Students will learn data analysis and model validation�techniques to assess modeling�data quality and statistical model fit.
Average GPA: 2.97
Grade distribution records: 41 students across 3 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 17 | 41.5% |
| B | 7 | 17.1% |
| C | 8 | 19.5% |
| D | 2 | 4.9% |
| F | 2 | 4.9% |
| W | 5 | 12.2% |
Based on 41 student grade records across 3 terms and 1 professor.
Instructors
- Dorothy Andrews 41 students, Average GPA 2.97