Probability and Statistics for Computer Science (eBook)

James L. Johnson (Autor)

eBook Download: PDF

2011 | 1. Auflage
760 Seiten
John Wiley & Sons (Verlag)
978-1-118-16596-6 (ISBN)

Infos

Comprehensive and thorough development of both probability and
statistics for serious computer scientists; goal-oriented: "to
present the mathematical analysis underlying probability
results"

Special emphases on simulation and discrete decision theory

Mathematically-rich, but self-contained text, at a gentle
pace

Review of calculus and linear algebra in an appendix

Mathematical interludes (in each chapter) which examine
mathematical techniques in the context of probabilistic or
statistical importance

Numerous section exercises, summaries, historical notes, and
Further Readings for reinforcement of content

Autor

James L. Johnson holds a PhD in mathematics from the University of Minnesota and has twenty-five years' experience in academic and industrial computer science. He is currently Professor of Computer Science at Western Washington University. He is also the author of Database: Models, Languages, Design.

Inhalt

Preface.

1. Combinatorics and Probability.

1.1 Combinatorics.

1.2 Summations.

1.3 Probability spaces and random variables.

1.4 Conditional probability.

1.5 Joint distributions.

1.6 Summary.

2. Discrete Distributions.

2.1 The Bernoulli and binomial distributions.

2.2 Power series.

2.3 Geometric and negative binomial forms.

2.4 The Poisson distribution.

2.5 The hypergeometric distribution.

2.6 Summary.

3. Simulation.

3.1 Random number generation.

3.2 Inverse transforms and rejection filters.

3.3 Client-server systems.

3.4 Markov chains.

3.5 Summary.

4. Discrete Decision Theory.

4.1 Decision methods without samples.

4.2 Statistics and their properties.

4.3 Sufficient statistics.

4.4 Hypothesis testing.

4.5 Summary.

5. Real Line-Probability.

5.1 One-dimensional real distributions.

5.2 Joint random variables.

5.3 Differentiable distributions.

5.4 Summary.

6. Continuous Distributions.

6.1 The normal distributions.

6.2 Limit theorems.

6.3 Gamma and beta distributions.

6.4 The X² and related distributions.

6.5 Computer simulations.

6.6 Summary.

7. Parameter Estimation.

7.1 Bias, consistency, and efficiency.

7.2 Normal inference.

7.3 Sums of squares.

7.4 Analysis of variance.

7.5 Linear regression.

7.6 Summary.

A. Analytical Tools.

B. Statistical Tables.

Bibliography.

Index.

Rezensionen

"Undoubtedly, this is an excellent and well-organized book." (Computing Reviews, August 27, 2008)

Produkt-Details

• Erscheint lt. Verlag: 9.9.2011
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Theorie / Studium
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Technik
• Schlagworte: Computer Science • Computer Science Special Topics • Informatik • Mathematik / Wahrscheinlichkeitstheorie, Statistik • Probability & Mathematical Statistics • Spezialthemen Informatik • Statistics • Statistik • Wahrscheinlichkeitsrechnung u. mathematische Statistik
• ISBN-10: 1-118-16596-9 / 1118165969
• ISBN-13: 978-1-118-16596-6 / 9781118165966