Basic probability : using Matlab /
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Libro |
| Lenguaje: | Inglés Español |
| Publicado: |
Boston :
PWS-KENT,
c1995
|
| Colección: | BookWare companion series
|
| Materias: | |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 02186nam a2200277 a 4500 | ||
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| 003 | AR-CdUBP | ||
| 005 | 20220310151737.0 | ||
| 008 | 151212s1995 us f 000 0 eng|d | ||
| 020 | |a 0-534-94536-8 | ||
| 040 | |a AR-CdUBP |b spa | ||
| 041 | |a spa | ||
| 100 | |a Pfeiffer, Paul E. | ||
| 245 | 1 | 0 | |a Basic probability : |b using Matlab / |c Paul E. Pfeiffer |
| 260 | |a Boston : |b PWS-KENT, |c c1995 | ||
| 300 | |a xx, 185 p. ; |c 22 cm. + |e 1 disquete | ||
| 490 | 0 | |a BookWare companion series | |
| 505 | 0 | |a 1. The probability of events. 1. The underlying model. 2. Minterms and boolean combinations of events. 3. Minterm probabilities and boolean combinations. 4. Appendix. The indicator function for a set. 2. Conditional probability, independence, and conditional independence. 1. Conditional probability. 2. Independence of events. 3. Conditional independence of events. 4. Bernoulli trials and the binomial distribution. Reinforcement exercises and exploration problems. 3. Random variables and distributions. 1. Review of concepts and notation. Matlab functions for some discrete distributions. 3. Matlab functions for some continuos distributions. 4. The multinomial distribution. 5. Summary data on some common distributions. 4. Simple random variables. 1. Representations using indicator functions. 2. Matlab implementation. 3. Probabilities, expectations, and functions of a random variable. 5. Jointly distributed simple random variables. 1. Extension of single-variable techniques. 2. Calculation of stantadard parameters for joint distributions. 3. Functions of a pair of random variables X,Y. 4. Independence of random variables. 5. General procedures for simple random variables. 6. Discrete approximation to continuos random variables. 1. Single random variable. 2. Jointly distributed pair. 7. Random sums. 1. A random number of random variables. 2. The generating function and moment generating function. 3. Some additional applications. 4. Appendix-some theoretical details. | |
| 650 | 4 | |a MATLAB | |
| 653 | |a INFORMATICA | ||
| 930 | |a INFORMATICA | ||
| 931 | |a 02266 |b UBP | ||
| 942 | |c BK | ||
| 945 | |a SMM | ||
| 984 | |a 519.6Matlab |b P476 | ||
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