This book 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. Intended for first-year graduate students, this book can be used for 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 for a variety of situations, and less concerned with formal optimality investigations.
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Review: Statistical InferenceUser Review - Jake Losh - Goodreads
A great, comprehensive resource for all things statistical (excluding regression analysis; you can't do it all). Clear prose, though the examples could use some work. Not recommended for stats newbies. Read full review
Review: Statistical InferenceUser Review - Goodreads
Read this book because it is the text for our PhD Econometrics I course, also mainly because it is recommended by Professor D, so first comes his comments on the book. "The standard PhD level first ...
Transformations and Expectations
Common Families of Distributions
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