Likelihood serves as a unifying concept in both the theory and practice of statistical science. This is, in a sense, inevitable when probability models are used as a basis for inference. While the key ideas were set out in Fisher in 1922, and further developed throughout the 1930s and 40s, it was the ubiquity of the personal computer and the development of general-purpose software that made likelihood-based inference the method of choice in a wide variety of applications.This book ...

The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the fo...

Why study the theory of experiment design? Although it can be useful to know about special designs for specific purposes, experience suggests that a particular design can rarely be used directly. It needs adaptation to accommodate the circumstances of the experiment. Successful designs depend upon adapting general theoretical principles to the spec