Taylor & Francis Ltd Statistical Inference 2nd edition

"This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions, and consequences, of previous concepts. It covers all the topics from a standard inference course, including distributions, random variables, data reduction, point estimation, hypothesis testing, interval estimation, and regression"-- Basics of probability to theory of statistical inference using techniques, definitions, concepts that are statistical, natural extensions, consequences, of previous concepts. Topics from a standard inference course: distributions, random variables, data reduction, point estimation, hypothesis testing, interval estimation, regression. This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features:The classic graduate-level textbook on statistical inferenceDevelops elements of statistical theory from first principles of probabilityWritten in lucid style accessible to anyone with some background in calculusCovers all key topics of a standard course in inferenceHundreds of examples throughout to aid understandingEach chapter includes extensive set of graduated exercisesStatistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less concerned with formal optimality considerations.