Results 251 to 260 of about 544,329 (286)
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2021
This chapter aims to provide the fundamentals of probability and statistics. This is an essential topic, and most of the advanced topics and majority of the applied examples are rooted in probabilistic-based simulations. First the differences between discrete and continuous random variables are explained.
Victor E. Saouma +1 more
+4 more sources
This chapter aims to provide the fundamentals of probability and statistics. This is an essential topic, and most of the advanced topics and majority of the applied examples are rooted in probabilistic-based simulations. First the differences between discrete and continuous random variables are explained.
Victor E. Saouma +1 more
+4 more sources
Nature, 1960
IF k 1(x) is any non-negative function in L 1 (− ∞, + ∞), let us write: for n = 2, 3, … Then the function: is defined almost everywhere (although it is possibly infinite for some, or all, x).
F. N. David, Ulf Grenander
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IF k 1(x) is any non-negative function in L 1 (− ∞, + ∞), let us write: for n = 2, 3, … Then the function: is defined almost everywhere (although it is possibly infinite for some, or all, x).
F. N. David, Ulf Grenander
openaire +2 more sources
Probability and Statistical Inference.
Applied Statistics, 1978Probability and Statistical Inference. By Robert V. Hogg and Elliot A. Tanis. New York, Macmillan, 1977. ix, 450 p. 24 cm. £11·25.
W. D. Ray +2 more
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2016
The Copenhagen interpretation of quantum mechanics, which is largely used today, is one consisting of probabilities and in order to make sense of how this applies to us as NMR spectroscopists we look at probability calculations and statistics. Also, for later use in relaxation, random or stochastic processes are modelled.
+4 more sources
The Copenhagen interpretation of quantum mechanics, which is largely used today, is one consisting of probabilities and in order to make sense of how this applies to us as NMR spectroscopists we look at probability calculations and statistics. Also, for later use in relaxation, random or stochastic processes are modelled.
+4 more sources
Computational Probability and Statistics
International Statistical Review / Revue Internationale de Statistique, 1972Freiberger, Walter, Grenander, Ulf
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Probability and Statistical Analysis.
Journal of the American Statistical Association, 1973James Ramsey +2 more
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2008
This chapter introduces probability theory—the mathematical theory of statistics—that gives the theoretical models and analytical tools for the organization, interpretation, and analysis of statistical data. Probability theory is applied in chemistry for the description of the collective behaviour of very large numbers of particles in statistical ...
openaire +1 more source
This chapter introduces probability theory—the mathematical theory of statistics—that gives the theoretical models and analytical tools for the organization, interpretation, and analysis of statistical data. Probability theory is applied in chemistry for the description of the collective behaviour of very large numbers of particles in statistical ...
openaire +1 more source