Gold Coast, Australia
Area of Study
Taught In English
ACSC12-200 - Mathematical Statistics AND INFT12-216 - Data Science
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3 - 4
Recommended U.S. Quarter Units4.5 - 6
Hours & Credits
This subject will cover the theory and practice of Advanced Regression Techniques. Topics such as regularisation, limited dependent variable models, generalised linear models, random and mixed effects models, splines, additive models and tree-based regression will be covered. The programming language R will be used in this course.Students should also have completed ECON12-200 Econometrics in addition to the other pre-requisites listed.
Learning Objectives1. Knowledge of the limitations of linear regression models and the ability to develop an appropriate regression model given the circumstance.
2. An ability to evaluate and choose between a variety of regression models.
3. Knowledge of the role of regularization and the ability to use the concept to develop a variety of regression models.
4. Ability to estimate limited dependent variable regression models.
5. Ability to estimate generalised linear models, random effects models and mixed effects models.
6. Ability to develop regression models utilising splines, kernals, polynomials and additive-methods.