In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

Id: 008463 Credits Min: 3 Credits Max: 3 Description Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of ...

Regression models to relate a scalar Y to a functional predictor X (t) are becoming increasingly common. Work in this area has concentrated on estimating a coefficient function, β(t), with Y related ...

Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...

Applied Regression Analysis and Generalized Linear Models Frees, E.W. (2010). Regression Modeling with Actuarial and Financial Applications Assessment Exam (70%, duration: 2 hours) in the January exam ...