Event Title
An Application of Logistic Regression in Estimation and Prediction
Location
CSU
Student's Major
Mathematics and Statistics
Student's College
Science, Engineering and Technology
Mentor's Name
Mezbahur Rahman
Mentor's Department
Mathematics and Statistics
Mentor's College
Science, Engineering and Technology
Description
Logistic regression is used in categorical response variable models. The explanatory variables could be categorical or in a continuous scale. Often, parameters are estimated and goodness-of-fit are studied in logistic models, but the ultimate usefulness of a logistic model depends on the prediction rule of the categorical response. Here we revisit all four aspects of the logistic regression using a data set. The four aspects are parameter estimation, goodness-of-fit of the model, prediction rule, and marginal effect of the factors.
An Application of Logistic Regression in Estimation and Prediction
CSU
Logistic regression is used in categorical response variable models. The explanatory variables could be categorical or in a continuous scale. Often, parameters are estimated and goodness-of-fit are studied in logistic models, but the ultimate usefulness of a logistic model depends on the prediction rule of the categorical response. Here we revisit all four aspects of the logistic regression using a data set. The four aspects are parameter estimation, goodness-of-fit of the model, prediction rule, and marginal effect of the factors.
