MAT 402 Applied Regression Analysis
This course provides the basic understanding of regression analysis and its application in real life. The course focuses on both theory and application of simple and multiple linear regression, and logistic regression. Topics covered are correlation, simple and multiple linear regression, model assumptions, parameter estimation, inference on regression model and parameters, regression diagnostic, model selection, multicollinearity, linear models with qualitative predictors, logistic regression, polynomial regression, and introduction to time series analysis. Students are required to analyze real-life datasets using statistical software.
Credits
4
Offered
once every two years