# Introduction to Applied Probability

In this case, the unit may be packaged and sold under another brand name at “bargain” prices. ... The manufacturer's return on the item is a random variable whose value is \$250 (first-line item), \$150 (second-line item), or \$50 (salvage ...

Author: Paul E. Pfeiffer

Publisher: Elsevier

ISBN: 9781483277202

Category: Mathematics

Page: 420

View: 831

Introduction to Applied Probability provides a basis for an intelligent application of probability ideas to a wide variety of phenomena for which it is suitable. It is intended as a tool for learning and seeks to point out and emphasize significant facts and interpretations which are frequently overlooked or confused by the beginner. The book covers more than enough material for a one semester course, enhancing the value of the book as a reference for the student. Notable features of the book are: the systematic handling of combinations of events (Section 3-5); extensive use of the mass concept as an aid to visualization; an unusually careful treatment of conditional probability, independence, and conditional independence (Section 6-4); the resulting clarification facilitates the formulation of many applied problems; the emphasis on events determined by random variables, which gives unity and clarity to many topics important for interpretation; and the utilization of the indicator function, both as a tool for dealing with events and as a notational device in the handling of random variables. Students of mathematics, engineering, biological and physical sciences will find the text highly useful.

# Energy Risk Modeling

Applied Modeling Methods for Risk Managers Nigel Da Costa Lewis. CHAPTER. 2. Introduction. to. Applied. Probability. for. Energy. Risk. Management. There are many instances where those involved in energy products must make decisions ...

Author: Nigel Da Costa Lewis

Publisher: Springer

ISBN: 9780230523784

Page: 247

View: 997

Energy Risk Modeling is a primer on statistical methods for managers, students and anybody interested in the field. Illustrated through elementary and more advanced statistical Methods, it is primarily aimed at those individuals who need a gentle introduction in how to go about using statistical methods for modeling energy price risk. Statistical ideas are presented by outlining the necessary concepts and illustrating how these ideas can be implemented. This is the first energy risk book on the market to focus specifically on the role of statistical methods. Its practical approach makes the book a very useful reference and an interesting read.

# Discrete time Asset Pricing Models in Applied Stochastic Finance

It is difficult to include in a moderate chapter an introduction to probability theory for a reader who has not undergone even an introductory course. However, we will try to provide some insight into probability concepts, ...

Author: P. C. G. Vassiliou

Publisher: John Wiley & Sons

ISBN: 9781118618660

Category: Mathematics

Page: 416

View: 180

Stochastic finance and financial engineering have been rapidly expanding fields of science over the past four decades, mainly due to the success of sophisticated quantitative methodologies in helping professionals manage financial risks. In recent years, we have witnessed a tremendous acceleration in research efforts aimed at better comprehending, modeling and hedging this kind of risk. These two volumes aim to provide a foundation course on applied stochastic finance. They are designed for three groups of readers: firstly, students of various backgrounds seeking a core knowledge on the subject of stochastic finance; secondly financial analysts and practitioners in the investment, banking and insurance industries; and finally other professionals who are interested in learning advanced mathematical and stochastic methods, which are basic knowledge in many areas, through finance. Volume 1 starts with the introduction of the basic financial instruments and the fundamental principles of financial modeling and arbitrage valuation of derivatives. Next, we use the discrete-time binomial model to introduce all relevant concepts. The mathematical simplicity of the binomial model also provides us with the opportunity to introduce and discuss in depth concepts such as conditional expectations and martingales in discrete time. However, we do not expand beyond the needs of the stochastic finance framework. Numerous examples, each highlighted and isolated from the text for easy reference and identification, are included. The book concludes with the use of the binomial model to introduce interest rate models and the use of the Markov chain model to introduce credit risk. This volume is designed in such a way that, among other uses, makes it useful as an undergraduate course.

# An Introduction to Applied Probability

Definition ( i ) If ( X , Y ) is a discrete bivariate random variable with joint probability distribution function p ( xi , Y ; ) , the conditional ... since { prix ( yj | x ; ) == 170 Applied Probability The Correlation Coefficient.

Author: Ian F. Blake

Publisher: Krieger Publishing Company

ISBN: PSU:000015286734

Category: Mathematics

Page: 552

View: 670

Designed for a curriculum that contains only 2 single one-semester course on probability. Covers the core of probability theory, considers sums of random variables, derives sampling distributions, and discusses the approximation of distributions. Includes nonstatistical and statistical applications such as hypothesis testing, confidence intervals, and regression analysis. Numerous worked examples throughout the text illustrate the material and each chapter concludes with a number of problems.

# Financial and Actuarial Statistics

In Chapter 1 basic statistical concepts and functions including an introduction to probability, random variables and their ... criteria are presented and applied to single risk models including investment and option pricing models, ...

Author: Dale S. Borowiak

Publisher: CRC Press

ISBN: 9780824748616

Category: Mathematics

Page: 357

View: 627

Based on a loss function approach, this comprehensive reference reviews the most recent advances in financial and actuarial modeling, providing a strong statistical background for advanced methods in pension plan structuring, risk estimation, and modeling of investment and options pricing. An authoritative tool supplying every conceptual model and

# An Introduction to Management Science Quantitative Approaches to Decision Making

With a uniform probability distribution, the following relationship between the random number and the associated value of the parts cost is used: Parts cost 5 a 1 r(b 2 a) (12.2) where r 5 random number between 0 and 1 a 5 smallest ...

Author: David R. Anderson

Publisher: Cengage Learning

ISBN: 9781305544666

Page: 912

View: 136

Reflecting the latest developments in Microsoft Office Excel 2013, Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, 14E equips readers with a sound conceptual understanding of the role that management science plays in the decision-making process. The trusted market leader for more than two decades, the book uses a proven problem-scenario approach to introduce each quantitative technique within an applications setting. All data sets, applications, and screen visuals reflect the details of Excel 2013 to effectively prepare you to work with the latest spreadsheet tools. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

# An Introduction to Management Science Quantitative Approaches to Decision Making

the possible values of the direct labor cost, the probability of generating a random number in any interval is equal ... the following Excel formula is used: Value of uniform random variable 5 lower bound 1 (upper bound 2 lower bound) 3 ...

Author: Jeffrey D. Camm

Publisher: Cengage Learning

ISBN: 9780357715574

Page: 912

View: 665

Gain a strong understanding of the role of management science in the decision-making process while mastering the latest advantages of Microsoft Office Excel 365 with Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams' AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, 16E. This market-leading edition uses a proven problem-scenario approach in a new full-color design as the authors introduce each quantitative technique within an application setting. You learn to apply the management science model to generate solutions and make recommendations for management. Updates clarify concept explanations while new vignettes and problems demonstrate concepts at work. All data sets, applications and screen visuals reflect the details of Excel 365 to prepare you to work with the latest spreadsheet tools. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

# Probability and Statistics for Finance

Discrete random variables are introduced in Chapter 9 where some of their parameters such as the mean and variance are defined. ... We conclude Chapter 9 with a discussion of the most commonly used discrete probability ...

Author: Svetlozar T. Rachev

Publisher: John Wiley & Sons

ISBN: 0470906324

Page: 672

View: 670

A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before. In order to keep up, you need a firm understanding of this discipline. Probability and Statistics for Finance addresses this issue by showing you how to apply quantitative methods to portfolios, and in all matter of your practices, in a clear, concise manner. Informative and accessible, this guide starts off with the basics and builds to an intermediate level of mastery. • Outlines an array of topics in probability and statistics and how to apply them in the world of finance • Includes detailed discussions of descriptive statistics, basic probability theory, inductive statistics, and multivariate analysis • Offers real-world illustrations of the issues addressed throughout the text The authors cover a wide range of topics in this book, which can be used by all finance professionals as well as students aspiring to enter the field of finance.

# Applied Probability and Stochastic Processes

Introduction. Is the world a well-ordered entirety, or a random mixture, which nevertheless is called world-order? ... rainfall intensity, electromagnetic noise levels, fluctuations of share prices, failure time points of technical ...

Author: Frank Beichelt

Publisher: CRC Press

ISBN: 9781482257670

Page: 347

View: 195

Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. It covers the theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates applications through the analysis of numerous practical examples. The author draws on his 50 years of experience in the field to give your students a better understanding of probability theory and stochastic processes and enable them to use stochastic modeling in their work. New to the Second Edition Completely rewritten part on probability theory—now more than double in size New sections on time series analysis, random walks, branching processes, and spectral analysis of stationary stochastic processes Comprehensive numerical discussions of examples, which replace the more theoretically challenging sections Additional examples, exercises, and figures Presenting the material in a student-friendly, application-oriented manner, this non-measure theoretic text only assumes a mathematical maturity that applied science students acquire during their undergraduate studies in mathematics. Many exercises allow students to assess their understanding of the topics. In addition, the book occasionally describes connections between probabilistic concepts and corresponding statistical approaches to facilitate comprehension. Some important proofs and challenging examples and exercises are also included for more theoretically interested readers.

# An Introduction to Applied Probability

Assume that the cost of an error when si is transmitted is 10 and the cost of an error when s2 is transmitted is 15. ... 6.66 . Samples of a population are used to estimate 242 Chapter 6 Random Processes and Common Probability Laws.

Author: Richard A. Roberts