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         Probability:     more books (100)
  1. Student Solutions Manual for Mendenhall/Beaver/Beaver's Introduction to Probability and Statistics, 12th by William Mendenhall, RobertJ. Beaver, et all 2005-01-03
  2. Introduction to Probability by Charles M. Grinstead, J. Laurie Snell, 1997-07-01
  3. A Course in Probability Theory Revised by Kai Lai Chung, 2000-01-15
  4. Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences) by John H. Aldrich, Forrest D. Nelson, 1984-11-01
  5. Probability and Random Variables: A Beginner's Guide by David Stirzaker, 1999-09-28
  6. Probability Theory by Alfred Renyi, 2007-05-11
  7. Student's Solution Manual Probability & Statistics by Morris H. DeGroot, Mark J. Schervish, 2002-05
  8. Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models (Quantitative Applications in the Social Sciences) by Tim F. Liao, 1994-06-30
  9. Probability Activities for Problem Solving & Skills Reinforcement by Robert Lovell, 1993
  10. Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences by J. Susan Milton, Jesse C Arnold, 2002-09-30
  11. Introduction to Probability Models: Operations Research, Volume II (with CD-ROM and InfoTrac®) by Wayne L. Winston, 2003-06-05
  12. The Probability Broach by L. Neil Smith, 2001-12-12
  13. Martingale Methods in Financial Modelling (Stochastic Modelling and Applied Probability) by Marek Musiela, Marek Rutkowski, 2007-06-11
  14. Probability and Finance: It's Only a Game! by Glenn Shafer, VladimirVovk, 2001-06-15

81. Sales Training & Selling Techniques Of High Probability® Selling
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82. HyperStat Online: Probability
Web based materials for teaching statistics"HSframes"

83. One Tailed Version Of Chebyshev's Inequality - By Henry Bottomley
Chebyshev's inequality with onetailed and unimodal versions, putting statistical limits on the dispersion of probability distributions.
Chebyshev's inequality
and a one-tailed version
Chebyshev's inequality states that for
which is equivalent to for
A one-tailed version of Chebyshev's inequality is that for
i.e. t
which is equivalent to for
Turning inequality into equality
Turning inequality into equality Proof of Chebyshev's inequality Proof of one-tailed version of Chebyshev's inequality ... Discussion and a new page with more thoughts Speculation on unimodal PDFs or go to a Mode-Mean inequality or Mode-Median-Mean relationships or some Statistics Jokes written by Henry Bottomley
Turning Chebyshev's inequality into an equality
P[X=m-k.s] = 1/(2.k ), P[X=m+k.s] = 1/(2.k ), and P[X=m] = 1-1/k
Note E(X)=m and Var (X)=s , sd(X)=s, so for this X k
The equality will in general only be achieved for a symmetric three-valued distribution. If the probabilities are p, 1-2p and p then equality is achieved when k=(2p) . A symmetric two-valued distribution is a special case with k=1. A chart showing this distribution for k=2 is below (return to top)
Turning one-tailed version of Chebyshev's inequality into an equality
becomes P[X=m+s.k] = 1/(1+k

84. Kluwer Academic Publishers - Journal Of Theoretical Probability
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85. GCSE Maths Revision Site
Features brief reviews of basic math concepts, from numbers and fractions to probability and statistics. Also, includes formula page and help forum.
Maths Coursework
14,000+ Essays to Download

6th Jun 2004
GCSE Maths
Home Revision Guides Discussion Forum Formula Sheet
Numbers Decimals Fractions Directed Numbers ... Variation
Shape and Space
Angles Circle Theorems Loci Shapes ... Transformations
Statistics and Probability
Averages Histograms Cum. Freq. Graphs Standard Deviation ... Probability
Travel Graphs Gradients Graphs
Factorising Algebraic Fractions Solving Equations Simultaneous Equations ... Flow Charts
Sin, Cos, Tan Pythagoras Sin and Cosine Formulae Bearings ... Congruency
Coursework Practise Questions
GCSE Maths Revision
Matthew Pinkney This site provides printable revision notes and help for GCSE maths students, covering the higher tier topics.
For more advanced topics, consult the A-Level section Search this Site: Revision Tips Links Revision Guides Support this site by buying revision materials via these links: You are visitor number (since Feb 2000): Please read the

86. What Are Statistics, Probability Theory, And Operations Research
Some definitions with a few examples, from the Dept. of Statistics at the Florida State University.
What are "Probability Theory," "Statistics," and "Operations Research?"
Probability theory
is the branch of mathematics which develops models for "chance variations" or "random phenomena." It originated as a rigorous discipline when mathematicians of the 17th century began calculating the odds in various games of chance. It was soon realized how to make applications of the theory they developed to the study of errors in experimental measurements and to the study of human mortality (for example, by life insurance companies). Probability theory is now a major branch of mathematics with widespread applications in science and engineering. A few examples are:
  • modeling the occurrence of sunspots to improve radio communication, modeling and control of congestion on highways, reliability theory to evaluate the chance that a space vehicle will function throughout a mission.
  • Statistics is the mathematical science of utilizing data about a population in order to describe it usefully and to draw conclusions and make decisions. The population may be a community, an organization, a production line, a service counter, or a phenomenon such as the weather. Statisticians develop models based on probability theory. They determine which probability model is correct for a given type of problem and they decide what kinds of data should be collected and examined. "Theoretical" statistics concerns general classes of problems and the development of general methodology. "Applied" statistics concerns the application of the general methodology to particular problems. This often calls for use of techniques of computer-based data analysis.

    probability and Data Analysis Concepts (NCTM Content Standard and NCEE StandardM4). Back to top. Statistics and probability Concepts. Activity
    These activities listed below are designed for either group or individual exploration into concepts from middle school mathematics. The activities are Java applets and as such require a java-capable browser. The activities are arranged according to the NCTM Principles and Standards for School Mathematics and the NCEE Performance Standards for Middle School Number and Operation Concepts (NCTM Content Standard and NCEE Standard M1) Geometry and Measurement Concepts (NCTM Content Standards and NCEE Standard M2) Function and Algebra Concepts (NCTM Content Standard and NCEE Standard M3) Probability and Data Analysis Concepts (NCTM Content Standard and NCEE Standard M4) Each activity comes with supplementary What How , and Why pages. These pages are accessed from the activity page. Each will open in a new window, when its button is pressed.
    What: gives background on the activity;
    How: gives instructions for the activity;
    Why: gives curriculum context for the activity.
    See WHAT'S NEW in Interactivate! New Activities that are fully functional but do not yet have supporting materials developed.

    88. Kluwer Academic Publishers - Potential Analysis
    (Kluwer) Devoted to the interactions between Potential Theory, probability Theory, Geometry and Functional Analysis. Abstracts and contents from vol.4 (1995). Full text to subscribers.
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    89. Probability And Geometry
    probability and Geometry. Abstract. The activity and two discussionsof this lesson connect probability and geometry. The
    Probability and Geometry
    The activity and two discussions of this lesson connect probability and geometry. The Polyhedra discussion leads to platonic solids, and the Probability and Geometry discussion leads to connections between angles, areas and probability. The subtle difference between defining probability by counting outcomes and defining probability by measuring proportions of geometrical characteristics is brought to light.
    Upon completion of this lesson, students will:
    • have practiced calculating probability
    • have seen how geometry can help solve probability problems
    • have learned about platonic solids
    The activities and discussions in this lesson address the following NCTM standards Data Analysis and Probability Understand and apply basic concepts of probability
    • understand and use appropriate terminology to describe complementary and mutually exclusive events
    • use proportionality and a basic understanding of probability to make and test conjectures about the results of experiments and simulations
    • compute probabilities for simple compound events, using such methods as organized lists, tree diagrams, and area models

    Two linked workshops within the Computation, Combinatorics and probability programme at the Isaac Newton Institute, Cambridge, UK. Part I Combinatorial and Computational Aspects of Statistical Physics; 2630 August 2002. Part II Random Graphs and Structures; 26 September 2002.
    Isaac Newton Institute for Mathematical Sciences, Cambridge, UK RANDOM STRUCTURES
    comprising the linked workshops
    26 - 30 AUGUST 2002
    2 - 6 SEPTEMBER 2002

    in association with the Newton Institute programme entitled Computation, Combinatorics and Probability
    (29 July to 20 December 2002)
    Abstracts Participants
    Memphis ), Martin Dyer ( Leeds ), Mark Jerrum ( Edinburgh ), Alan Sokal ( New York ) and Peter Winkler ( Bell Labs Theme of Workshop
    The heading "random structures" is intended to cover both the finite (random graphs, partial orders, etc.) and infinite (configurations of some physical model on an infinite lattice). Our aim is to bring together combinatorialists, probabilists, physicists and theoretical computer scientists to engage in an interdisciplinary meeting that will study random structures from various directions. Structure
    There will be two linked workshops: Combinatorial and computational aspects of statistical physics and Random graphs and structures . The overarching theme that unites these two is that of phase transition, broadly interpreted. A rough distinction between the two workshops might be that the first deals with phase transitions in infinite systems (e.g., the Ising model on the 2-dimensional square lattice), and the second with "phase transitions" in finite structure (e.g., random graphs or random partial orders). However, this distinction is certainly not intended to be a hard-and-fast. Computational questions - such as the extent to which phase transitions may coincide with the boundary between tractable and intractable - will certainly be addressed.

    91. Project Euclid Journals
    Nail Akar, Khosrow Sohraby; 557569 view abstract. A finite-time ruin probabilityformula for continuous claim severities. 2004 Applied probability Trust.

    92. Stuart Russell
    Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.
    Stuart Russell
    Computer Science Division

    Soda Hall

    University of California

    Berkeley, CA 94720-1776
    russell at Other useful pointers:

    93. Project Euclid Journals
    Anuj Srivastava, Eric Klassen; 4356 view abstract. General Applied probability. Correction.324-324 view abstract. © 2004 Applied probability Trust.

    94. Risk Coronary Artery Disease
    Diagram of the heart and the arteries, discussion about calcification and calculation of the likelihood of CAD.
    Published June 2000
    Revised Septermber 2001
    Probability of Coronary Artery Disease
    Medicine is a science of uncertainty and an art of probability
    Coronary Artery Calcification
    CT detection Atherosclerotic heart disease is the number one cause of death. Methods of detecting coronary artery disease prior to fatal events are needed so that appropriate measures can be taken to reduce risk. Anatomic studies have established that coronary calcification is invariably located near areas of advanced atherosclerotic disease. A direct relation between the extent of coronary calcification and the severity of stenotic lesions or frequency of myocardial infarction is consistently observed in autopsy series. The more extensive the calcification, the more frequent and more severe the degree of stenosis. This relationship is recognized in all age groups and both sexes, but is more marked in younger patients.
    CT and in particular, electron-beam CT (EBCT) is the most sensitive radiographic method to detect coronary artery calcification. The value of EBCT can be summarized as follows:

    95. Probability Distributions
    Common probability Distributions. This Compendium instead. A Compendiumof Common probability Distributions. Printing Notes. Compendium
    Common Probability Distributions
    This Compendium describes distributions appropriate for the modeling of random data. Although similar summaries may be found in textbooks, this reference exhibits some unusual features, viz.,
    • The number of distributions (56) is large, including
      • Continuous distributions (30)
        Symmetric (11)
        Skewed (19)
      • Continuous binary mixtures (17)
      • Discrete distributions (5)
      • Discrete binary mixtures (4)
    • All formulas are shown in their fully-parametrized form, not the standard form.
    • Many of the formulas given are seldom described.
    • Random variate generation is included where feasible.
    • Each (two-page) entry is readily printable in full 600-dpi resolution (see below), and/or
    • The entire file (549K, pdf) may be downloaded and printed to give a complete reference book
      [but please
    Data Modeling
    Regress+ The latter is a software tool for mathematical modeling and, hence, this Compendium shares the same focus. All of the distributions described here may be used with Regress+ to model empirical data.

    96. Section On Applied Probability
    A subdivision of the Institute for Operations Research and the Management Sciences (INFORMS) concerned with the application of probability theory to systems that involve random phenomena, for example, manufacturing, communication network, computer network, service, and financial systems.

    97. Statistical Inference On The TI-83/86/89
    Contains problems and solutions on general topics of probability distributions, confidence intervals, hypothesis testing, analysis of variance, and correlation analysis. Detailed survey sampling projects are also included.
    Statistical Inference on the TI-83+/86/89 This site contains typical problems and solutions on the general statistics topics of probability distributions, confidence intervals, hypothesis testing, analysis of variance, and correlation analysis. Detailed survey sampling projects are also included.
    The materials here are designed to supplement a general descriptive statistics course. Throughout, the problems are worked with programs suited for the TI-83+, TI-86, and TI-89 calculators. By using the calculator programs to work the problems, virtually all of the formula memorization, hand calculation, and textbook charts are taken out of the course. Thus, students can concentrate on understanding the results, drawing conclusions, and learning when and how to apply the proper procedure and program to solve a problem. These materials were developed by David K. Neal , Department of Mathematics, Western Kentucky University, Bowling Green, KY 42101 USA: Download Instructions Setting Up the TI-86 Setting Up the TI-89 ...
    Basic Statistics

    (No programs required)
    Program Topics
    Discrete Distributions
    The Binomial Random Variable The Poisson Random Variable The Geometric Random Variable The Negative Binomial Random Variable ...
    Combined Discrete Distribution Program

    Continuous Distributions The Normal Distributions The t-Distributions The Chi-Square Distributions The F-Distributions ...
    Combined Continuous Distribution Programs

    Confidence Intervals Confidence Interval for Mean of an Arbitrary Population Confidence Interval for Mean of a Normally Distributed Population Confidence Interval for a Proportion Confidence Interval for the Difference of Means Between Two Independent Arbitrary Populations ... Confidence Interval for Ratio of Variances of Independent Normal Populations
    Hypothesis Tests

    THE ANNALS. of. probability. AN OFFICIAL JOURNAL OF THE. Note that the Annals ofprobability and the Annals of Applied probability are listed under Statistics.
    I NSTITUTE OF M ATHEMATICAL ... TATISTICS As of January 1, 2003, Steven Lalley, Department of Statistics, University of Chicago, is the new editor of the Annals All new submissions should be sent to him. (See the new Annals web page for submission information.) All papers submitted prior to January 1, 2003 will continue to be handled by the 2000-2002 editorial board, and all correspondence regarding these papers should continue to be sent to 2000-2002 Editorial Staff Electronic Access to Recent Issues of the Annals This access is provided through Project Euclid. If your institution is a subscriber and you are using an institutional computer, you should have access. If you are a subscriber to any IMS journal, you should have access, but you must register. You should have received information on how to register at the time the journal first became available. For further information on access see the IMS web page. Electronic Access to Past Issues of the Annals This access is provided through the electronic journal storage project JSTOR. You may not have access to JSTOR unless your institution is a subscriber.

    99. Math Forum - Ask Dr. Math Archives: Middle School Probability
    From the archives of the Math Forum, a web forum, questions about various probability problems, and the answers.
    Ask Dr. Math
    Middle School Archive

    Dr. Math Home
    Elementary Middle School High School ... Dr. Math FAQ
    This page:



    See also the
    Dr. Math FAQ
    and probability in the real world Internet Library probability MIDDLE SCHOOL About Math Algebra equations factoring expressions ... Word Problems
    Browse Middle School Probability Stars indicate particularly interesting answers or good places to begin browsing. See also Middle School Statistics. Selected answers to common questions: Coin tossing.
    Drawing Marbles
    A jar contains 2 red, 3 blue, and 4 green marbles. Niki draws one marble from the jar, and then Tom draws a marble. What is the probability that Niki will draw a green marble and Tom will draw a blue marble?
    Gambler's Fallacy
    My co-worker prefers to bet the same set of five lottery numbers every time, but I say that the probability is the same if you randomly select any set five numbers for the same period of time. Who is right?
    Math Symbol for C
    I am puzzled by one symbol of typing math. What does the upper case letter C mean? As in (2C1) (3C1) / (47C2) = 6/1081.
    Odds Slang for Probability?

    100. Functional Analysis Group
    The interests of the group are diverse ranging from topological aspects of the geometry of Banach spaces, through operator systems, to topics bordering on probability and differential equations.

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