Statistical Inference - Casella, George; Berger, Roger L (London CRC Press, 2024)
This book builds theoretical statistics from thefirst principles of probability theory. Startingfrom the basics of probability, the authorsdevelop the theory of statistical inferenceusing techniques, definitions and conceptsthat are statistical and are natural extensionsand consequences of previous concepts.Intended for first-year graduate students, thisbook can be used for students majoring instatistics who have a solid mathematicsbackground. It can also be used in a way thatstresses the more practical uses of statisticaltheory, being more concerned withunderstanding basic statistical concepts andderiving reasonable statistical procedures for avariety of situations and less concerned withformal optimality investigations.FEATURES Offers new coverage of randomnumber generation, simulation methods,bootstrapping, EM algorithm, p-values androbustness.Includes new sections on "Logistic Regression"and "Robust Regression"Restructures material for clarity purposesContains updated and expanded Exercises Key Features
Keywords: Mathematical statistics; Probability theory; Random variables