Residual plots can be used to validate assumptions about the regression model. Figure 1: Residual plots are helpful in assessments of nonlinear trends and heteroscedasticity. A formal test of lack ...

The course covers the probability, distribution theory and statistical inference ... Most powerful tests. Neyman-Pearson lemma. Linear regression. Least-squares estimation. Generalised linear models.

“The statistician knows...that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive ...

The course provides a precise and accurate treatment of probability, distribution theory and statistical inference ... goodness-of-fit tests and contingency tables. A treatment of linear regression ...

In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

In this paper, we propose a functional linear regression model in the space of probability density functions. We treat a cross-sectional distribution of individual earnings as an infinite dimensional ...