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Tanis and Hogg's Probability and Statistical Inference is a comprehensive book on statistical mathematics for undergraduate and postgraduate mathematicians studying an advanced course in probability and mathematics. The book introduces students to probability and statistics through an eye for variation. It shows readers how variation exists in every aspect of our lives, and how statistics and probability exist to study this variation. The students will learn about nonparametric methods, Bayesian methods, and Quality Improvement, conditional distributions and functions of random variables, and they will also grasp the approximations of distributions using the central limit theorem. The book is an indispensable resource for anyone sitting for their actuarial exams or studying various statistical methods for use in quality improvement. About the Authors Robert V. Hogg is the Professor Emeritus at the University of Iowa, where he teaches actuarial sciences and statistics. He studied at the University of Illinois, where he obtained his B.A. in mathematics, and then went on to pursue his postgraduate and doctoral studies at the University of Iowa. He has also written: Introduction of Mathematical Statistics, Applied Statistics for Engineers and Physical Scientists, and A Brief Course in Mathematical Statistics. He has received the Mathematical Association of America Award for Distinguished Teaching, and the Governor's Science Medal for Teaching, for his excellence in the field of teaching. Elliot Tanis is the Professor Emeritus of mathematics at Hope College, where he teaches statistics. He graduated from the University of Iowa and has also written Probability and Statistics: Explorations with MAPLE. He has received the Hope's Outstanding Professor Educator award (HOPE) for his excellence in teaching at the college.