Mathematical Methods of Statistics
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Harald Cramér
About this book
Harald Cramér’s classic synthesis of statistical mathematical theory—an invaluable resource for students and practitioners alike
In the 1930s, as British and American statisticians were developing the science of statistical inference, French and Russian probabilitists transformed the classical calculus of probability into a rigorous and pure mathematical theory. In this incisive and authoritative book, Harald Cramér unites these two major lines of development, providing a masterly exposition of the mathematical methods of modern statistics that set the standard in the field still followed today.
Requiring only a working knowledge of undergraduate mathematics, this self-contained book begins with an introduction to the fundamental concept of a distribution and of integration with respect to a distribution. It goes on to discuss the general theory of random variables and probability distributions, the theory of sampling, statistical estimation, and tests of significance.
Blending lucid and accessible writing with mathematical rigor, Mathematical Methods of Statistics belongs on the shelf of anyone interested in statistical methods and remains the standard reference on the subject today.
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Frontmatter
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Preface
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Table of Contents
xi - First Part. Mathematical Introduction
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Chapters 1–3. Sets of Points
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Chapters 4–7. Theory of Measure and Integration in R1.
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Chapters 8–9. Theory of Measure and integration in Rn
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Chapters 10–12. Various Questions
89 - Second Part. Random Variables and Probability Distributions
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Chapters 13–14. Foundations
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Chapters 15–20. Variables and distributions in R1
166 - Third Part. Statistical Interference
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Chapters 25–26. Generalities
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Chapters 27–29. Sampling Distributions
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Chapters 30–31. Test of Significance, I.
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Chapters 32–34. Theory of Estimation
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Chapters 35–37. Test of Significance, II.
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Tables 1–2. The Normal Distribution
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Table 3. The χ2 -Distribution
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Table 4. The t-Distribution
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List of References
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Index
571