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About 10,000 papers for “Applied probability”

Applied Probability

(:unkn) unknown · TIB Repositorium · 2003

[no abstract available]

Cited by 0Open access

Applied Probability

MacColl, L. · Proceedings of symposia in applied mathematics · 1957

Cited by 4

Applied Probability.

I. G. Evans, W. A. Thompson · Journal of the Royal Statistical Society Series A (General) · 1970

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Applied Probability

Paul E. Pfeiffer · BiblioBoard Library Catalog (Open Research Library) · 2009

This is a "first course" in the sense that it presumes no previous course in probability. The mathematical prerequisites are ordinary calculus and the elements of matrix algebra. A few standard series and integrals are used, and double integrals are evaluated as iterated integrals. The reader who can evaluate simple integrals can learn quickly from the examples how to deal with the iterated integrals used in the theory of expectation and conditional expectation. Appendix B provides a convenient compendium of mathematical facts used frequently in this work. And the symbolic toolbox, implementing MAPLE, may be used to evaluate integrals, if desired.In addition to an introduction to the essential features of basic probability in terms of a precise mathematical model, the work describes and employs user defined MATLAB procedures and functions (which we refer to as m-programs, or simply programs) to solve many important problems in basic probability. This should make the work useful as a stand-alone exposition as well as a supplement to any of several current textbooks.Most of the programs developed here were written in earlier versions of MATLAB, but have been revised slightly to make them quite compatible with MATLAB 7. In a few cases, alternate implementations are available in the Statistics Toolbox, but are implemented here directly from the basic MATLAB program, so that students need only that program (and the symbolic mathematics toolbox, if they desire its aid in evaluating integrals).Since machine methods require precise formulation of problems in appropriate mathematical form, it is necessary to provide some supplementary analytical material, principally the so-called minterm analysis. This material is not only important for computational purposes, but is also useful in displaying some of the structure of the relationships among events.

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Probability Applied

Nick Firoozye, Fauziah Ariff · Palgrave Macmillan UK eBooks · 2016

Probability, statistics and stochastic differential equations have had considerable success in finance and economics. We have discussed the evolution of the concept of risk in modern finance in Chapter 2. Here we will touch on many of the major modelling-based developments in modern risk and finance and their statistical underpinnings. We present a broad overview of probabilistic methods in use in banking and finance today and how probabilistic thinking has moved the sector forward significantly.KeywordsRisk MeasureOption PriceOptimal PortfolioStochastic VolatilityAsset ReturnThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Introductory Applied Probability.

Wallace E. Franck, G. P. Beaumont · Journal of the American Statistical Association · 1984

Chapter 1: Introduction. Law of Unintended Consequences. Enterprise Excellence. Enterprise Excellence Model. Continuous Measurable Improvement. Achieving Enterprise Excellence. Key Points. Chapter 2: Managing and Leading Enterprise Excellence. Lead People - Manage Things. Management Systems. Leading Enterprise Excellence. The Leadership Model . Leading and Managing Teams. Effective Meetings. Understanding and Overcoming Resistance to Change. The 3Cs: Communication, Cooperation, and Coordination. Key Points. Chapter 3: Enterprise Excellence Deployment. Enterprise Excellence Infrastructure . Deployment Measurement, Analysis and Reporting. Enterprise Excellence Deployment Planning. Establishing Enterprise Excellence Policies, Guidelines and Infrastructure. Key Points. Chapter 4: Enterprise Excellence Implementation. Management and Operations Plans. Enterprise Excellence Projects. Enterprise Excellence Project Decision Process . Planning The Enterprise Excellence Project. Tollgate Reviews. Project Notebook. Key Points. Chapter 5: Listening to the Voice of the Customer. Voice of the Customer (VOC). Answering the Voice of the Customer. Technology Development. Development of Products, Services and Processes. Quality Function Deployment. CDOV Process. Key Points. Chapter 6: Define (Knowing and Understanding Your Processes). Understanding Process Variation. Acquire All Process Documentation. Process Mapping. Value Stream Mapping. Value Stream Analysis. Process Walkthrough. Failure Modes and Effects Analysis. Key Points. Chapter 7: Measure. Process Measurement. Statistical Process Control. Statistical Process Control Charts. Control Charts Analysis. Variation. Type of Control Charts & Applications. Attribute Control Charts. Process Capability Analysis. Measurement Systems Evaluation (MSE). Gauge Reproducibility & Repeatability (R&R). Transactional MSE. Key Points. Chapter 8: Analyze and Improve Effectiveness. Analysis of Variance. One-Way ANOVA. Two-Way ANOVA. Linear Contrasts. Design of Experiments. Key Points. Chapter 9: Analyzing and Improving Efficiency. 5S Process. The Seven Forms of Waste. Takt Time. Cycle Time. Routing Analysis. Spaghetti Diagram. Work Content Analysis. Process Availability Analysis. Process Yield Measures. Cycle Time. Just in Time. Kanban. Mixed-Model Production. A B C Material Handling. Workable Work. Workload Balancing. One Piece Flow. Work Cell Design. Kanban Sizing. Key Points. Chapter 10: Control and Continuous Measurable Improvement. Management Systems. Statistical Process Control. Visual Controls. Graphic Work Instructions. Mistake Proofing (Poka-Yoke). Single-Minute Exchange of Die (SMED). Total Productive Maintenance. Rapid Improvement Events. Continuous Measurable Improvement. Key Points. Appendix A: Bibliography. Appendix B: Glossary. Appendix C: Basic Math Symbols. Appendix D: List of Acronyms.

Cited by 5

Advances in Applied Probability is currently published by Applied Probability Trust.

Vinod Sharma · 2012

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