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25 Remote Warehouse Mathematics- Probability and Statistics

Statistical and Probabilistic Methods in Actuarial Science

by

Statistical and Probabilistic Methods in Actuarial Science Cover

 

Synopses & Reviews

Publisher Comments:

It encourages students to use the statistical software package R to check examples and solve problems.

Book News Annotation:

Boland's (University College Dublin, Ireland) text covers many of the diverse methods in applied probability and statistics, building on the reader's existing basic knowledge of probability and statistics to establish a solid and thorough understanding of the methods. In particular, the text emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used, including models for losses and collective risk, reserving and experience rating, credibility estimation, and measures of security for risk. Also included are basic introductions to generalized linear models, decision-making and game theory. Suitable as a text for students preparing for careers in insurance, actuarial science and finance, and as a text and reference for insurance analysts. Annotation ©2007 Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Providing a solid foundation of both theory and methods Statistical and Probabilistic Methods in Actuarial Science offers a unified and accessible introduction to probability and statistics for students aspiring to careers in actuarial science and insurance. This book presents practical examples of applications, specifically to general insurance, financial decision making, and risk analysis. It includes discussions of computing methods, focusing in particular on the value of simulation techniques. To facilitate student understanding, each chapter features numerous exercises. Selected solutions are contained in an appendix, and a separate solutions manual is available for lecturers.

Synopsis:

Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students? existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used.

?

Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of Markov chain methods. The final chapters discuss generalized linear models and decision and game theory.

Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.

Synopsis:

Covering many of the diverse methods in applied probability and statistics, this book builds on readers' existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used. The applications to general insurance include loss distributions and collective risk models, reserving and experience rating, credibility estimation, and security measures of risk. The book examines generalized linear models, credibility theory, game theory, and simulation techniques and contains numerous worked examples and problems.

Product Details

ISBN:
9781584886952
Author:
Boland, Philip J.
Publisher:
Chapman & Hall/CRC
Author:
Boland, Boland J.
Subject:
Mathematics
Subject:
Insurance
Subject:
Probability & Statistics - General
Subject:
Actuarial science
Subject:
Mathematics | Probability and Statistics
Series:
Interdisciplinary Statistics
Publication Date:
20070331
Binding:
Hardcover
Language:
English
Illustrations:
Y
Pages:
351
Dimensions:
9.32x6.46x.98 in. 1.43 lbs.

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Related Subjects

Business » Insurance
Reference » Science Reference » Technology
Science and Mathematics » Chemistry » Biochemistry
Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Statistical and Probabilistic Methods in Actuarial Science New Hardcover
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Product details 351 pages Chapman & Hall/CRC - English 9781584886952 Reviews:
"Synopsis" by , Providing a solid foundation of both theory and methods Statistical and Probabilistic Methods in Actuarial Science offers a unified and accessible introduction to probability and statistics for students aspiring to careers in actuarial science and insurance. This book presents practical examples of applications, specifically to general insurance, financial decision making, and risk analysis. It includes discussions of computing methods, focusing in particular on the value of simulation techniques. To facilitate student understanding, each chapter features numerous exercises. Selected solutions are contained in an appendix, and a separate solutions manual is available for lecturers.
"Synopsis" by , Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students? existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used.

?

Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of Markov chain methods. The final chapters discuss generalized linear models and decision and game theory.

Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.

"Synopsis" by , Covering many of the diverse methods in applied probability and statistics, this book builds on readers' existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used. The applications to general insurance include loss distributions and collective risk models, reserving and experience rating, credibility estimation, and security measures of risk. The book examines generalized linear models, credibility theory, game theory, and simulation techniques and contains numerous worked examples and problems.
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