000			01839nam a22002057a 4500
003			OSt
005			20241119172853.0
008			181116b ||||| |||| 00| 0 eng d
020			_a9788126518050
040			_cGift _aICTS-TIFR
050			_aQA273
100			_aWilliam Feller
245			_aAn introduction to probability theory and its applications
260			_aU.K.: _bJohn Wiley & Sons, _c[c1957]
300			_a509 p
505			_a1. Introduction: The Nature of Probability Theory. 2. The Sample Space. 3. Elements of Combinatorial Analysis. 4. Fluctuations in Coin Tossing and Random Walks. 5. Combination of Events. 6. Conditional Probability. 7. The Binomial and 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. Renewal Theory. 15. Random Walk and Ruin Problems. 16. Markov Chains. 17. Algebraic Treatment of Finite Markov Chains. 18. The Simplest Time-Dependent Stochastic Processes.
520			_aAn Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory. Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way. --- summary provided by publisher
650			_aMathematics
942			_2lcc _cBK
999			_c2098 _d2098