probability theory in English
His main research topics were number theory, probability theory and mathematical statistics.
Use "probability theory" in a sentence
1. He dealt with algebra, analysis, mechanics and probability theory.
2. I had studied statistics, probability theory, mathematical modeling, experimental design.
3. Risk associated with project outcomes is usually handled with probability theory.
4. Pascal's development of probability theory was his most influential contribution to mathematics.
5. In probability theory and statistics, the zeta distribution is a discrete probability distribution.
6. One version of the probability theory ofCarnap permits us to establish a priori probabilities.
7. Beyond probability theory, they are applied in domains ranging from number theory to physics.
8. Furthermore, we survey separation theorems for Biconvex functions which are mostly applied in probability theory.
9. Lyapunov contributed to several fields, including differential equations, potential theory, dynamical systems and probability theory.
10. Alongside his teaching responsibilities, Bunyakovsky made significant scientific contributions in number theory and probability theory.
11. The Kolmogorov Axioms are the foundations of probability theory introduced by Andrey Kolmogorov in 1933
12. The properties of Z-transforms (below) have useful interpretations in the context of probability theory.
13. What is The Axiomatic Definition of Probability? Axiomatic probability is a unifying probability theory in Mathematics
14. By symmetry, .The Binomial coefficient is important in probability theory and combinatorics and is sometimes also denoted
15. Yushchenko worked on probability theory, algorithmic languages and programming languages, and developing methods of automated data processing systems.
16. Compared to the current structure of probability theory, his work only lacked the technical condition of sigma additivity.
17. Marczewski's main fields of interest were measure theory, descriptive set theory, general topology, probability theory and universal algebra.
18. The fascinating story of cryptography requires us to understand two very old ideas related to number theory and probability theory.
19. Inferences on mathematical statistics are made under the framework of probability theory, which deals with the analysis of random phenomena.
20. In general, there are two points of view with regard to the relationship between probability theory and algebra and geometry.
21. In probability theory and statistics, the Jensen–Shannon divergence is a method of measuring the similarity between two probability distributions.
22. Markov then resumed his teaching activities and lectured on probability theory and the calculus of differences until his death in 1922.
23. There is also a specialised master program in statistics (major and minor), including courses on probability theory, mathematical finance and actuarial science.
24. The number e itself also has applications to probability theory, where it arises in a way not obviously related to exponential growth.
25. Prior to large experimentations on the teaching of probability theory, it appeared useful to observe some students working for a fairly long time.
26. However, it should be noted that Pascal and Fermat, though doing important early work in probability theory, did not develop the field very far.
27. The Bayesian approach to data analysis provides a powerful way to handle uncertainty in all observations, model parameters, and model structure using probability theory
28. And essentially what Bayes did was to provide a mathematical way using probability theory to characterize, describe, the way that scientists find out about the world.
29. The Convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and its applications to statistics and stochastic processes.
30. Meanwhile, the set condition that pedestrian crossing transform from non-signal control mode to signal control mode was analyzed by using probability theory and gap acceptance theory.
31. Contiguous data storage, in computer science; Contiguity (probability theory) Contiguity (psychology) Contiguous distribution of species, in biogeography; Geographic Contiguity of territorial land; Contiguous zone in territorial waters; See also
32. Variance and Covariance are mathematical terms frequently used in statistics and probability theory. Variance refers to the spread of a data set around its mean value, while a …
33. In probability theory, Markov's inequality gives an upper bound for the probability that a non-negative function of a random variable is greater than or equal to some positive constant.
34. This public-key cryptosystem endocing technique uses a mixing system based on polynomial algebra and recuction modulo two numbers while the decoding technique uses an unmixing system whose validity depends on elementary probability theory.
35. As of 2015, IMPA does research in algebra, analysis, differential geometry, partial differential equations, computer graphics, fluid dynamics, holomorphic dynamics, mathematical economics, symplectic geometry, algebraic geometry, optimization, probability theory, dynamical systems, and ergodic theory.
36. Bimodal - of a distribution; having or occurring with two modes statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters unimodal - having a single mode
37. Biserial correlation - a correlation coefficient in which one variable is many-valued and the other is dichotomous Biserial correlation coefficient statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
38. In probability theory and statistics, a Covariance matrix (also known as auto-Covariance matrix, dispersion matrix, variance matrix, or variance–Covariance matrix) is a square matrix giving the Covariance between each pair of elements of a given random vector.Any Covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the Covariance of each