A basic course in measure and probability : theory for applications Originating from the authors own graduate course at the University of North Carolina this material has been thoroughly tried and tested over many years making the book perfect for a two term course or for self study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians including Lebesgue integration limit theorems in probability martingales and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics econometrics finance meteorology machine learning and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm take off point for them as they specialize in areas that exploit mathematical machinery