000			01384cam a22002291 4500
999			_c1498 _d1498
001			2644
005			20200820100446.0
008			791005m19571971nyua b 000 0 eng
020			_a0471257095 (v. 2)
040			_cDLC
082	0	0	_a519.2 _bF318
100	1		_aFeller, William,
245	1	3	_aAn introduction to probability theory and its applications _c/ William Feller
250			_a2nd ed.
260			_aNew York : _bWiley, _c[1957-71]
300			_a2 v. _billus. _c24 cm.
490	0		_aA Wiley publication in mathematical statistics
500			_aincludes index
650		0	_aProbabilities.
942			_cBK
505	0		_a1. Introduction: the nature of probability theory 2. The sample space 3. Elements of combinatorial analysis 4. Fluctuations in coin tossing and random wales 5. Combination of events 6. Conditional probability. Stochastic independence 7. The binomial and the poisson distributions 8. The normal approximation to the binomial distribution 9. Unlimited sequences of bernoulli trials 10. Random variables; expectation 11. Laws of large numbers 12. Integral valued variables. Generating functions 13. Compound distributions. Branching processes 14. Recurrent events. The renewal equation 15. Random walk and ruin problems 16. Markov chains 17. Algebraic treatment of finite markov chains 18. The simplest time-dependent stochastic processes