By Egan J. Chernoff, Gale L. Russell (auth.), Egan J. Chernoff, Bharath Sriraman (eds.)
ISBN-10: 9400771541
ISBN-13: 9789400771543
ISBN-10: 940077155X
ISBN-13: 9789400771550
This quantity presents an important, present and huge research of probabilistic pondering from a couple of mathematicians, arithmetic educators, and psychologists. The paintings of fifty eight contributing authors, investigating probabilistic pondering around the globe, is encapsulated in 6 prefaces, 29 chapters and six commentaries. finally, the 4 major views offered during this quantity (Mathematics and Philosophy, Psychology, Stochastics and arithmetic schooling) are designed to symbolize probabilistic considering in a better context.
Read Online or Download Probabilistic Thinking: Presenting Plural Perspectives PDF
Best mathematics_1 books
Dieses erfolgreiche einf? hrende Lehrbuch liegt nun in der 10. Auflage vor. Es zeichnet sich durch eine exakte und anschauliche Darstellung aus. Der Lehrstoff ist klar gegliedert und intestine strukturiert. Er wird durch eine F? lle von Beispielen und Abbildungen veranschaulicht und vertieft. Zahlreiche Aufgaben mit L?
Probabilistic Expert Systems (CBMS-NSF Regional Conference Series in Applied Mathematics)
Probabilistic professional platforms emphasizes the fundamental computational ideas that make probabilistic reasoning possible in specialist platforms. the major to computation in those structures is the modularity of the probabilistic version. Shafer describes and compares the important architectures for exploiting this modularity within the computation of previous and posterior chances.
Surveys in Differential-Algebraic Equations III
The current quantity includes survey articles on quite a few fields of Differential-Algebraic Equations (DAEs), that have frequent purposes in managed dynamical structures, particularly in mechanical and electric engineering and a powerful relation to (ordinary) differential equations. the person chapters supply studies, shows of the present nation of analysis and new suggestions in - Flexibility of DAE formulations - Reachability research and deterministic worldwide optimization - Numerical linear algebra equipment - Boundary worth difficulties the consequences are offered in an obtainable sort, making this booklet compatible not just for lively researchers but in addition for graduate scholars (with a superb wisdom of the elemental rules of DAEs) for self-study.
- Theory of Linear Operators in Hilbert Space: Volume II
- Cours de mathématiques Tome 4 Equations différentielles Intégrales multiples
- Leçons de géométrie élémentaire I (géométrie plane)
- Simulation-Driven Modeling and Optimization: ASDOM, Reykjavik, August 2014
Additional info for Probabilistic Thinking: Presenting Plural Perspectives
Sample text
Modelling in probability and statistics—key ideas and innovative examples. In J. Maaß, & J. ), Real-world problems for secondary school students—case studies (pp. 1–44). Rotterdam: Sense Publishers. , & Kapadia, R. (1991). A probabilistic perspective. In R. Kapadia, & M. ), Mathematics education library: Vol. 12. Chance encounters (pp. 27–71). Dordrecht: Kluwer Academic. Buffon, G. L. (1777). Essai d’arithmetique morale. In G. L. Buffon, Histoire naturelle générale et particulière (Suppl. 4). Paris: Imprimérie Royale.
London: Griffin. Bellhouse, D. R. (2000). De Vetula: a medieval manuscript containing probability calculations. International Statistical Review, 68(2), 123–136. Berger, J. O. (1993). Statistical decision theory and Bayesian analysis. New York: Springer. Bernoulli, D. (1738/1954). Specimen theoriae novae de mensura sortis. Commentarii Academiae Scientiarum Imperialis Petropolitanae, 5, 175–192. , Exposition of a new theory on the measurement of risk. Econometrica, 22, 23–36. Bernoulli, J. (1713/1987).
Pascal and Fermat’s approach sheds light on the correct application of what they termed to be the ‘favourable to possible rule’, but they made less progress in trying to formally define the concept of probability. They used probability pragmatically as the equal likelihood of outcomes in games of chance, which seemed to be intuitively obvious to them. Hence the emergence of the classical a priori theory (APT) of probability, which later was linked to the principle of indifference discussed below, based on the ideas of Laplace.