Probability and Statistics for Computer Science (Hardcover)
暫譯: 計算機科學的機率與統計 (精裝版)

James L. Johnson

Probability and Statistics for Computer Science (Hardcover)

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商品描述

A unique probability study for computer science students

While many computer science curricula include only an introductory course on general probability, there is a recognized need for further study of this mathematical discipline within the specific context of computer science. Probability and Statistics for Computer Science develops introductory topics in probability with this particular emphasis, providing computer science students with an invaluable resource in their continued st udies and professional research.

James Johnson’s text begins with the basic definitions of probability distributions and random variables and then elaborates their properties and applications. Probability and Statistics for Computer Science treats the most common discrete and continuous distributions, showing how they find use in decision and estimation problems, and constructs computer algorithms for generating observations from the various distributions. This one-of-a-kind resource also:

  • Includes a thorough and rigorous development of all the necessary supporting mathematics
  • Provides an opportunity to reconnect applications with the theoretical concepts of distributions introduced in prerequisite courses
  • Gathers supporting topics in an appendix: set theory, limit processes, real number structure, Riemann-Stieltjes integrals, matrix transformation, and determinants
  • Uses computer science examples from computer science such as client-server performance evaluation and image processing

The author also addresses a variety of supporting topics, such as estimation arguments with limits, properties of power series, and Markov processes. Johnson’s text proves an ideal resource for computer science students and practitioners interested in a probability study specific to their field

Table of Contents：

Preface.

1. Combinatorics and Probability.

2. Discrete Distributions.

3. Simulation.

4. Discrete Decision Theory.

5. Real Line-Probability.

6. Continuous Distributions.

7. Parameter Estimation.

Appendix A. Analytical Tools.

Appendix B. Statistical Tables.

Bibliography.

Index.

商品描述(中文翻譯)

計算機科學學生的獨特機率研究

雖然許多計算機科學課程僅包含一般機率的入門課程，但在計算機科學的特定背景下，進一步研究這一數學學科的需求已被認可。《計算機科學的機率與統計》發展了機率的入門主題，並特別強調這一點，為計算機科學學生在持續學習和專業研究中提供了寶貴的資源。

詹姆斯·約翰遜的文本從機率分佈和隨機變數的基本定義開始，然後詳細闡述它們的性質和應用。《計算機科學的機率與統計》處理了最常見的離散和連續分佈，展示了它們在決策和估計問題中的應用，並構建了從各種分佈生成觀察值的計算機算法。這本獨特的資源還：

- 包含所有必要的支持數學的徹底和嚴謹的發展
- 提供了一個機會，將應用與先修課程中介紹的分佈理論概念重新聯繫起來
- 在附錄中收集支持主題：集合論、極限過程、實數結構、黎曼-斯蒂爾傑斯積分、矩陣變換和行列式
- 使用計算機科學中的例子，如客戶端-伺服器性能評估和影像處理

作者還涉及各種支持主題，如帶有極限的估計論證、冪級數的性質和馬爾可夫過程。約翰遜的文本對於對其領域特定的機率研究感興趣的計算機科學學生和從業者來說，是一個理想的資源。

目錄：

前言。

1. 組合學與機率。
2. 離散分佈。
3. 模擬。
4. 離散決策理論。
5. 實數線-機率。
6. 連續分佈。
7. 參數估計。
附錄 A. 分析工具。
附錄 B. 統計表。
參考文獻。
索引。

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