Jane M. Horgan - Probability with R
Здесь есть возможность читать онлайн «Jane M. Horgan - Probability with R» — ознакомительный отрывок электронной книги совершенно бесплатно, а после прочтения отрывка купить полную версию. В некоторых случаях можно слушать аудио, скачать через торрент в формате fb2 и присутствует краткое содержание. Жанр: unrecognised, на английском языке. Описание произведения, (предисловие) а так же отзывы посетителей доступны на портале библиотеки ЛибКат.
- Название:Probability with R
- Автор:
- Жанр:
- Год:неизвестен
- ISBN:нет данных
- Рейтинг книги:3 / 5. Голосов: 1
-
Избранное:Добавить в избранное
- Отзывы:
-
Ваша оценка:
Probability with R: краткое содержание, описание и аннотация
Предлагаем к чтению аннотацию, описание, краткое содержание или предисловие (зависит от того, что написал сам автор книги «Probability with R»). Если вы не нашли необходимую информацию о книге — напишите в комментариях, мы постараемся отыскать её.
is used throughout the text, not only as a tool for calculation and data analysis, but also to illustrate concepts of probability and to simulate distributions. The examples in
cover a wide range of computer science applications, including: testing program performance; measuring response time and CPU time; estimating the reliability of components and systems; evaluating algorithms and queuing systems.
Chapters cover: The R language; summarizing statistical data; graphical displays; the fundamentals of probability; reliability; discrete and continuous distributions; and more.
This second edition includes:
improved R code throughout the text, as well as new procedures, packages and interfaces; updated and additional examples, exercises and projects covering recent developments of computing; an introduction to bivariate discrete distributions together with the R functions used to handle large matrices of conditional probabilities, which are often needed in machine translation; an introduction to linear regression with particular emphasis on its application to machine learning using testing and training data; a new section on spam filtering using Bayes theorem to develop the filters; an extended range of Poisson applications such as network failures, website hits, virus attacks and accessing the cloud; use of new allocation functions in R to deal with hash table collision, server overload and the general allocation problem. The book is supplemented with a Wiley Book Companion Site featuring data and solutions to exercises within the book.
Primarily addressed to students of computer science and related areas,
is also an excellent text for students of engineering and the general sciences. Computing professionals who need to understand the relevance of probability in their areas of practice will find it useful.
TABLE 18.2 Comparison of Normal and Binomial Probabilities with
and
TABLE 18.3 Comparison of Normal and Poisson Probabilities with 
Function Figure 3.16 The Line of Best Fit Figure 3.17 The Scatter of the Training Data Figure 3.18 The Line of Best Fit for the Training Data Figure 3.19 Differences Between Observed and Estimated
Values in the Testing... Figure 3.20 Plots of Four Data Sets with Same Means and Standard Deviations
Components each with Reliabil...Figure 8.6 Reliability of a Parallel System with
ComponentsFigure 8.7 Reliability of
Subsystems in Series with Component Reliability of...Figure 8.8 Reliability of
Subsystems in Series with Component Reliability of...
Figure 10.6 Simulated and Theoretical Geometric Distributions with
Figure 10.7 Amy's Winnings in 50 PlaysFigure 10.8 Geometric Distribution: Number of Inspections (
) to the First Def...
and
Figure 11.7 Number of Defectives per Sample of 20 with 
= 10,
= 0.1Figure 12.5 Hypergeometric and Binomial pdfs with
= 10,
= 0.1
Figure 13.3 Binomial pdf
Figure 13.4 Binomial pdf
Figure 13.5 Poisson pdf
Figure 13.6 Poisson pdfsFigure 13.7 Poisson cdfsFigure 13.8 Bug DetectionFigure 13.9 Simulated Web Hits: Poisson Distribution,
Figure 13.10 Simulated Web Hits: Poisson Distribution, 
= 10 from Batches o...Figure 14.2 Simulated Number of Defectives in Samples of
drawn from Large Ba...Figure 14.3 Simulated Number of Defectives in Samples of
drawn from Large Ba...Figure 14.4 Operating Characteristic CurvesFigure 14.5 Ideal Operating Characteristic Curve which Rejects Batches contain...Figure 14.6 Average Outgoing QualityFigure 14.7 Operating Characteristic CurveFigure 14.8 Average Sample Size