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Optimal Statistical Decisions
  • Language: en
  • Pages: 511

Optimal Statistical Decisions

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists.

Probability and Statistics
  • Language: en
  • Pages: 834

Probability and Statistics

  • Type: Book
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  • Published: 2013
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  • Publisher: Unknown

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Probability & Statistics, Fourth Edition, was written for a one- or two-semester probability and statistics course. This course is offered primarily at four-year institutions and taken mostly by sophomore and junior level students majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

Probability and Statistics
  • Language: en
  • Pages: 834

Probability and Statistics

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Probability & Statistics was written for a one- or two-semester probability and statistics course. This course is offered primarily at four-year institutions and taken mostly by sophomore and junior level students majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. The full text downloaded to your c...

Probability and Statistics
  • Language: en
  • Pages: 744

Probability and Statistics

The revision of this well-respected text presents a balance of the classical and Bayesian methods. The theoretical and practical sides of both probability and statistics are considered. New content areas include the Vorel- Kolmogorov Paradox, Confidence Bands for the Regression Line, the Correction for Continuity, and the Delta Method.

Student Solutions Manual for Probability and Statistics
  • Language: en

Student Solutions Manual for Probability and Statistics

  • Type: Book
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  • Published: 2011-01-14
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  • Publisher: Pearson

This manual contains completely worked-out solutions for all the odd-numbered exercises in the text.

A Modern Introduction to Probability and Statistics
  • Language: en
  • Pages: 488

A Modern Introduction to Probability and Statistics

Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Optimal Statistical Decisions
  • Language: en
  • Pages: 489

Optimal Statistical Decisions

  • Type: Book
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  • Published: 1993
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  • Publisher: Unknown

None

Bayesian Analysis and Uncertainty in Economic Theory
  • Language: en
  • Pages: 234

Bayesian Analysis and Uncertainty in Economic Theory

No descriptive material is available for this title.

Statistics in the Law
  • Language: en

Statistics in the Law

  • Categories: Law
  • Type: Book
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  • Published: 2023
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  • Publisher: Unknown

The bulk of this book is concerned with individual cases ranging over a wide variety of topics, such as electronic draw poker (does it require skill to play), employment discrimination, driving while black (did the New Jersey State Police disproportionately stop blacks), jury representativeness, and others.

All of Statistics
  • Language: en
  • Pages: 446

All of Statistics

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.