LECTURES PROBABILITY & STATISTICS GRADUATE-LEVEL ECONOMICS

Sound knowledge of rigorous probability and statistics methods is essential to pursue graduate studies in economics. These sorts of tools are largely required to conduct research in modern fields of economics such as economic theory, empirical economics, experimental economics, or data science for economics.

These notes provide an intuitive roadmap to navigate graduate-level courses in mathematical probability and statistics for economists. Each chapter presents questions prevalent on each topic and lays out the state-of-the-art theoretical frameworks used to address such questions. The book offers a diverse array of solved examples to help gain intuitions on abstract concepts, as well as unsolved exercises to stimulate the readers' training in such concepts. The book presents the theoretical side of probability and statistics in a rather concise way and stresses the importance of motivating examples and observations.

Contents:
Probability:Probability ModelsRandom Variables and Their DistributionsMoments of DistributionsMoment-Generating and Characteristic FunctionsParticular DistributionsCombinatoricsStatistical Inference:Convergence of DistributionsPoint EstimationHypothesis TestingInterval Estimation
Readership: Graduate students and instructors of courses in probability and statistics in graduate economics programs.

Key Features: Emphasis on the sorts of tools that are required to conduct research in economics. The concepts developed in the book can be readily applied to address questions of interest in economics Rigorous theoretical ideas of probability theory, such as concepts of measure theory, are presented in intuitive ways with the aid of solved examples A practical and concise approach is taken to help readers directly obtain the sorts of tools needed to answer questions of interest in graduate studies in economics