Emphasizes importance of likelihood function in statistical theory and applications, discusses it in the context of biology and ecology. Bayesian and frequentist methods use the likelihood function and provide differing but related insights - examined here through review of basic methodology and integrated use of these approaches in case studies. "The book under review is targeted at applied scientists with a focus on explaining the applications of different statistical methods based on the likelihood... This book provides particular emphasis on the interpretability aspects of statistics for its use by an applied scientist for the analysis of their research data without abackground in statistics or mathematics. To me, the book mostly succeeds to fulfil this objective. Although it is surely difficult to provide a comprehensive overview of all modelling issues and the corresponding statistical methods under one book of around 200 pages, the author has done a pretty good job of covering the most important issues related to likelihood based inference... In this book, the author has avoided the question of superiority of inferiority of any particular statistical paradigm and discussed the applications of both frequentist and Bayesian methods simultaneously to answer a scientific question by combining both results... All of the case studies are nicely present to provide ideas of different issues in a data analysis process and their solutions based on likelihood based statistical procedures... Overall, this is a great effort in the difficult task of writing a book on statistical inferences for applied scientists from different disciplines and I want to thank the author for such a great job."- Abhik Ghosh, ISCB December 2019