An introduction to more than 10 regression models that handle different types of datasets. In addition to the OLS Regression models, we will cover: Logistic Regression, Multinomial Logistic Regression, Poisson Regression, Quasi Poisson Regression, Negative Binomial Regression, Quantile Regression, Polynomial Regression, Lasso Regression, Ridge Regression, Elastic Net Regression, Principal Components Regression (PCR), Partial Least Squares (PLS) Regression, Ordinal Regression, Support Vector Regression, and Cox Regression.
About our speaker: Dr. Chang received his Ph.D. in Industrial Engineering/Operations Research from Texas Tech University and served as a teaching assistant there. Prior to teaching at Wilmington University, Dr. Chang taught graduate Operations Research I, Operations Research II, and Statistics for Managers courses at Saint Peter’s College, Jersey City, New Jersey. Dr. Chang also taught undergraduate Statistics I and Statistics II courses at Philadelphia University, Philadelphia, Pennsylvania in 2007 and 2008. Currently, Dr. Chang teaches Business Statistics, Forecasting for Business Analytics, and Optimization for Business Analytics courses.
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