The course emphasizes likelihood-based inference and offers a comprehensive exploration of key topics, including sufficiency and exponential family of distributions, moments and moment-generating functions, minimum variance unbiased estimation, and methods of transformation. Furthermore, students will gain in-depth knowledge on the likelihood principle and maximum likelihood estimation, maximum likelihood asymptotic theory, and likelihood-based hypothesis testing. The course also addresses loss and risk functions, model selection, and pre-testing, equipping learners with the necessary tools to make informed decisions in various management contexts. By the end of this course, students will possess a understanding of the core theoretical principles that underpin statistical estimation and testing techniques in the realm of business and economics.