61. What Are Statistics, Probability Theory, And Operations Research Some definitions with a few examples, from the Dept. of Statistics at the Florida State University. http://stat.fsu.edu/undergrad/statinf2.html

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.

62. THE ANNALS OF PROBABILITY THE ANNALS. of. probability. AN OFFICIAL JOURNAL OF THE. Note that the Annals ofprobability and the Annals of Applied probability are listed under Statistics. http://www.math.wisc.edu/~annprob/

THE ANNALS of PROBABILITY A N O FFICIAL J OURNAL OF THE 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 annprob@math.wisc.edu 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.

63. Infinite Dimensional Analysis, Quantum Probability And Related Topics (IDAQP) World Scientific. Contents, abstracts of all volumes; full text to institutional subscribers. http://www.worldscinet.com/idaqp/idaqp.shtml

What's New New Journals Browse Journals Search ... Mathematics Infinite Dimensional Analysis, Quantum Probability and Related Topics (IDAQP) In the past few years the fields of infinite dimensional analysis and quantum probability have undergone increasingly significant developments and have found many new applications, in particular, to classical probability and to different branches of physics. The number of first-class papers in these fields has grown at the same rate. This is currently the only journal which is devoted to these fields. More Feature Articles (Free Online Sample Issue) Volume 5, Number 1, March 2002 Click here to access the full text articles now. On the EPR-Chameleon-Experiment L. Accardi, K. Imafuku and M. Regoli Splitting of Poisson Noise and Lévy Processes on Real Lie Algebras N. Privault The Riesz Representation Theorem on Infinite Dimensional Spaces and Its Applications Y.-J. Lee and C.-Y. Shih Stochastic Evolution as a Quasiclassical Limit of a Boundary Value Problem for Schrödinger Equations V. P. Belavkin and V. N. Kolokol'tsov

64. Project Euclid Journals General Applied probability. On Dufresne's relation between the probability lawsof exponential functionals of Brownian motions with different drifts. http://projecteuclid.org/Dienst/UI/1.0/Journal?authority=euclid.aap

65. Computation, Combinatorics And Probability Research programme at the Isaac Newton Institute, Cambridge UK. Themes include Randomised algorithms; Phase transitions in statistical physics and computer science; Random graphs and structures. August December 2002. http://www.newton.cam.ac.uk/programs/CMP/cmp.html

Seminars This week Next week Workshops Participants Long Stay Short Stay Contacts Mailing list ... Newton Institute Isaac Newton Institute for Mathematical Sciences Computation, Combinatorics and Probability 29 Jul20 Dec 2002 Organisers: Professor Martin Dyer (Leeds) Professor Mark Jerrum (Edinburgh) , Dr Peter Winkler (Bell Labs) Programme theme As Computer Science has matured as a discipline, its relationships with mathematics have become both more wide ranging and more profound. The programme will explore two particularly fruitful interfaces between computer science and mathematics, namely those with combinatorics and probability theory. Although no interdisciplinary work within the broad area delineated by the title will be excluded, the following themes will receive special emphasis. Randomised algorithms. The design and analysis of algorithms that make random choices; also deterministic algorithms when run on random instances.The theoretical basis here includes the study of parameters connected with random walks on graphs and the relationships between them.

66. Project Euclid Journals For nearly four decades, the Journal of Applied probability has provideda forum for original research and reviews in applied probability. http://projecteuclid.org/Dienst/UI/1.0/Journal?authority=euclid.jap

67. Mathinfo2000 Aims to bring together researchers in theoretical computer science and mathematics. Topics include trees, stochastic processes, large deviations, branching processes, random walks, discrete probability, enumerative and analytical combinatorics, analysis of algorithms, performance evaluation, and combinatorial optimization. Versailles, France, September 1820, 2000. http://www.prism.uvsq.fr/complex/confs/mathinfo2000/index-anglais.html

Colloquium on Mathematics and Computer Science : Algorithms, Trees, Combinatorics and Probabilities Call For Papers September 18-20, 2000 45, avenue des Etats-Unis 78035 Versailles cedex - France Scientific Committee Organisation Committee Electronic mail : mathinfo@prism.uvsq.fr Scope of the Colloquium Call For Papers Appel a communications (postscript) Invited papers Sponsors List of accepted papers Scientific program ... Version francaise Important dates : March 15, 2000 : Deadline for submission of papers (10 pages). May 24, 2000 : Decision of the scientific committee June 15, 2000 : Final version of accepted papers Official languages : English and French Registration Accomodation Conference site LAMA

68. Probability Theory As Extended Logic A monumental online book by the late ET Jaynes on Bayesian inference. Also has a number of related Category Science Math Statistics Bayesian Analysis......Louis probability Theory As Extended Logic. Last Modified 1213-2002 Tom LoredoWe have Tom Loredo's excellent tutorial on probability theory. http://bayes.wustl.edu/

Probability Theory As Extended Logic Last Modified Edwin T. Jaynes was one of the first people to realize that probability theory, as originated by Laplace, is a generalization of Aristotelian logic that reduces to deductive logic in the special case that our hypotheses are either true or false. This web site has been established to help promote this interpretation of probability theory by distributing articles, books and related material. As Ed Jaynes originated this interpretation of probability theory we have a large selection of his articles, as well as articles by a number of other people who use probability theory in this way: E. T. Jaynes: articles , and the first three chapters from Jaynes' book on probability theory are now online as a pdf file or as a postscript file. As the publication date for Jaynes' book approaches we will update these pages to point you to the appropriate web sites to purchase the final copy of the book. A typed publication quality version of his unpublished book titled "Probability Theory, With Applications in Science and Engineering" that was being prepared for publication in the mid 1970's is available. Additionally, the most recent copy of his

69. Probabilistic Causation Probabilistic Causation designates a group of philosophical theories that aim to characterize the relationship between cause and effect using the tools of probability theory. A primary motivation for the development of such theories is the desire for a theory of causation that does not presuppose physical determinism. http://plato.stanford.edu/entries/causation-probabilistic/

version history HOW TO CITE THIS ENTRY Stanford Encyclopedia of Philosophy A B C D ... Z content revised SEP Probabilistic Causation ceteris paribus clause more precise. This article traces these developments, as well as recent, related developments in causal modeling. Issues within, and objections to, probabilistic theories of causation will also be discussed. 1. Introduction and Motivation 1.1 Regularity Theories 1.2 Imperfect Regularities 1.3 Indeterminism ... Related Entries 1. Introduction and Motivation 1.1 Regularity Theories an object, followed by another, and where all the objects similar to the first, are followed by objects similar to the second Suggested Readings: Hume (1748), especially section VII. 1.2 Imperfect Regularities The first difficulty is that most causes are not invariably followed by their effects. For example, it is widely accepted that smoking is a cause of lung cancer, but it is also recognized that not all smokers develop lung cancer. (Likewise, not all non-smokers are spared the ravages of that disease.) By contrast, the central idea behind probabilistic theories of causation is that causes raise the probability of their effects; an effect may still occur in the absence of a cause or fail to occur in its presence. Thus smoking is a cause of lung cancer, not because all smokers develop lung cancer, but because smokers are

70. Applied Probability Society Of INFORMS A subdivision of the Institute for Operations Research and the Management Sciences (INFORMS) concerned Category Science Math probability...... http://www.ie.psu.edu/aps/

71. Theory Of Probability And Its Applications Theory of probability and Its Applications. Edited by Will Klump. Theoryof probability and Its Applications is a translation of the http://www.siam.org/journals/tvp/Tvp.htm

search: Theory of Probability and Its Applications Edited by Will Klump Theory of Probability and Its Applications is a translation of the Russian journal Teoriya Veroyatnostei i ee Primeneniya, which contains papers on the theory and application of probability, statistics, and stochastic processes. Click HERE for the latest issues. Questions/Comments about our Web pages? Use our suggestion box or send e-mail to the Online Services Manager. About SIAM Membership Journals SIAM News ... Laura B. Helfrich , Online Services Manager Updated: DJC

72. Law, Probability And Risk http://www3.oup.co.uk/lawprj/

Select a journal... Adelphi Papers African Affairs Age and Ageing Alcohol and Alcoholism American Journal of Epidemiology American Law and Economics Review American Literary History Annals of Botany Annals of Occupational Hygiene Annals of Oncology Applied Linguistics Australasian Journal of Philosophy Behavioral Ecology Bioinformatics Biometrika Biostatistics BJA: British Journal of Anaesthesia BJA: CEPD Reviews Brain Brief Treatment and Crisis Intervention British Journal of Aesthetics British Journal of Criminology British Jnl. for the Philosophy of Sci. British Journal of Social Work British Medical Bulletin BWP Update Cambridge Journal of Economics Cambridge Quarterly Carcinogenesis Cerebral Cortex Chemical Senses Classical Quarterly Classical Review Clinical Psychology: Science and Practice Communication Theory Community Development Journal Computer Bulletin Computer Journal Contemporary Economic Policy Contributions to Political Economy ELT Journal EMBO Journal Early Music Economic Inquiry English Historical Review Environmental Practice Epidemiologic Reviews ESHRE Monographs Essays in Criticism European Journal of International Law European Journal of Orthodontics European Journal of Public Health European Review of Agricultural Economics European Sociological Review Family Practice Forestry Forum for Modern Language Studies French History French Studies Glycobiology Greece and Rome Health Education Research Health Policy and Planning Health Promotion International History Workshop Journal Holocaust and Genocide Studies Human Communication Research

73. 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. http://www.btinternet.com/~se16/hgb/cheb.htm

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 /Var(X)) 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 becomes 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

74. Probability Puzzles probability. amoeba. You sample one hundred balls with replacement and they are allwhite. What is the probability that all the balls are white? Solution bayes. http://einstein.et.tudelft.nl/~arlet/puzzles/probability.html

Probability amoeba A jar begins with one amoeba. Every minute, every amoeba turns into 0, 1, 2, or 3 amoebae with probability 25% for each case ( dies, does nothing, splits into 2, or splits into 3). What is the probability that the amoeba population eventually dies out? Solution apriori An urn contains one hundred white and black balls. You sample one hundred balls with replacement and they are all white. What is the probability that all the balls are white? Solution bayes One urn contains black marbles, and the other contains white or black marbles with even odds. You pick a marble from an urn; it is black; you put it back; what are the odds that you will draw a black marble on the next draw? What are the odds after n black draws? Solution birthday/line At a movie theater, the manager announces that they will give a free ticket to the first person in line whose birthday is the same as someone who has already bought a ticket. You have the option of getting in line at any time. Assuming that you don't know anyone else's birthday, that birthdays are distributed randomly throughtout the year, etc., what position in line gives you the greatest chance of being the first duplicate birthday? Solution birthday/same.day

75. AN INTRODUCTION TO PROBABILITY AN INTRODUCTION TO probability. probability ACTIVITIES Page AuthorJim Albert (c) albert@bayes.bgsu.edu Document http//wwwmath http://www-math.bgsu.edu/~albert/m115/probability/outline.html

AN INTRODUCTION TO PROBABILITY What is a probability? the relative frequency view the subjective view Measuring probabilities by means of a calibration experiment ... PROBABILITY ACTIVITIES Page Author: Jim Albert (c) albert@bayes.bgsu.edu Document: http://www-math.bgsu.edu/~albert/m115/probability/outline.html Last Modified: November 24, 1996

76. Probability Distributions Common probability Distributions. This Compendium instead.. A Compendiumof Common probability Distributions. Printing Notes. Compendium http://www.geocities.com/~mikemclaughlin/math_stat/Dists/Compendium.html

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.

77. Probability Chapter 4 probability. Other Sites. Contents. Analysis Tools Binomialprobabilities by B. Narasimhan Instructional Demos Normal approximation http://www.ruf.rice.edu/~lane/hyperstat/probability.html

Chapter 4: Probability Other Sites Contents Analysis Tools Binomial probabilities by B. Narasimhan Instructional Demos Normal approximation to binomial by David Lane Bayes' theorem by John Pezzullo Lets make a deal game by Webster West Lets make a deal game by Stat Dept, U. of Illinois Binomial distribution by B. Narasimhan Binomial distribution by Berrie Zielman Normal approximation to binomial by Keith Dear Normal approximation to the binomial by Berrie Zeilman Dice rolling simulation by Charles Stanton Hypergeometric distribution by Charles Stanton Poisson distribution by Charles Stanton Text Introduction to probability probability distributions independence and tree models conditional probability ... Binomial distribution by Keith Dear Probability More probability by P. B. Stark Probability discrete distributions by H. J. Newton, J. H. Carroll, N. Wang, and D. Whiting

78. Probability: What Are Your Chances?-NCES Students' Classroom Ever wonder how often an event might happen? Try What Are Your Chances?Gain a little knowledge about probability. JavaScript is http://nces.ed.gov/nceskids/probability/

JavaScript is currently turned off on your machine. "The probable is what usually happens" - Aristotle. What many people refer to as 'good luck' can actually be explained by a little knowledge about probability and statistics. Our dice game allows you to see how increasing or decreasing the number of dice rolls effects an outcome. So give it a try, choose the number of rolls you would like to make and roll the dice! "It is a truth very certain that when it is not in our power to determine what is true we ought to follow what is most probable" - Descartes Number of Rolls: Try More Activities! Students' Classroom Home Help Site Index ... NCES Home

79. Probability Sampling A probability sampling method is any method of sampling that utilizessome form of random selection. In order to have a random selection http://trochim.human.cornell.edu/kb/sampprob.htm

Home External Validity Sampling Terminology Statistical Sampling Terms [ Probability Sampling ] Nonprobability Sampling A probability sampling method is any method of sampling that utilizes some form of random selection . In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection. Some Definitions Before I can explain the various probability methods we have to define some basic terms. These are: N = the number of cases in the sampling frame n = the number of cases in the sample N C n = the number of combinations (subsets) of n from N f = n/N = the sampling fraction That's it. With those terms defined we can begin to define the different probability sampling methods. Simple Random Sampling The simplest form of random sampling is called simple random sampling . Pretty tricky, huh? Here's the quick description of simple random sampling:

80. HyperStat Online: Probability Web based materials for teaching statistics http://davidmlane.com/hyperstat/probability.html

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