ABSTRACT
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book provides upper level undergraduate and graduate students, who are in statistics and related areas, an advanced textbook in the area of linear models. It also provides a useful desk reference and state-of-the-art examination of this area to researchers in academia and government who are engaged in statistical research and to statisticians and scientists in industry who perform statistical analyses for projects related to linear models. The concept of linear models is widely accepted and has extensive applications in many fields such as the biological, social, and medical sciences. The book explains the up-to-date theories, methods, and applications in linear models. It presents some preliminary results on matrix theory and multivariate normal and its related distributions. Various linear models are also introduced through real examples. The book describes statistical inferences such as parameter estimation, hypotheses testing, confidence interval and prediction.
