Introduction to Probability with Statistical Applications / by Géza Schay

By:

Schay, Géza

Material type: Text

TextPublication details: U S A : Birkhauser, 2007.Edition: 2nd ed. 2016Description: 313pISBN:

9783319306209

Subject(s):

DDC classification:

519.5 SCH

Contents:

Introduction -- The Algebra of Events -- Combinatorial Problems -- Probabilities -- Random Variables -- Expectation, Variance, Moments -- Some Special Distributions -- The Elements of Mathematical Statistics.

Summary: Now in its second edition, this textbook serves as an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. More classical examples such as Montmort's problem, the ballot problem, and Bertrand's paradox are now included, along with applications such as the Maxwell-Boltzmann and Bose-Einstein distributions in physics. Key features in new edition: * 35 new exercises * Expanded section on the algebra of sets * Expanded chapters on probabilities to include more classical examples * New section on regression * Online instructors' manual containing solutions to all exercises <advanced undergraduate="" and="" graduate="" students="" in="" computer="" science,="" engineering,="" other="" natural="" social="" sciences="" with="" only="" a="" basic="" background="" calculus="" will="" benefit="" from="" this="" introductory="" text="" balancing="" theory="" applications.advanced="" applications. <advanced undergraduate="" and="" graduate="" students="" in="" computer="" science,="" engineering,="" other="" natural="" social="" sciences="" with="" only="" a="" basic="" background="" calculus="" will="" benefit="" from="" this="" introductory="" text="" balancing="" theory="" applications.review="" of="" the="" first="" edition: This textbook is a classical and well-written introduction to probability theory and statistics... the book is written 'for an audience such as computer science students, whose mathematical background is not very strong and who do not need the detail and mathematical depth of similar books written for mathematics or statistics majors.' ... Each new concept is clearly explained and is followed by many detailed examples... numerous examples of calculations are given and proofs are well-detailed." (Sophie Lemaire, Mathematical Reviews, Issue 2008 m).

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Holdings
Item type	Current library	Home library	Call number	Status	Date due	Barcode
Book	Dept. of Statistics Processing Center	Dept. of Statistics	519.5 SCH (Browse shelf(Opens below))	Available		STA10040

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Previous	519.5 ROB Monte Carlo Statistical methods/	519.5 SAL Statistics for people who(think they) hate statistics	519.5 SAM Stochastic modeling and mathematical statistics : a text for statisticians and quantitative scientists	519.5 SCH Introduction to Probability with Statistical Applications /	519.5 SEA Linear models /	519.5 SHA Statistics for scientists and engineers /	519.5 SIL Statistical inference /	Next

Now in its second edition, this textbook serves as an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. More classical examples such as Montmort's problem, the ballot problem, and Bertrand's paradox are now included, along with applications such as the Maxwell-Boltzmann and Bose-Einstein distributions in physics. Key features in new edition: * 35 new exercises * Expanded section on the algebra of sets * Expanded chapters on probabilities to include more classical examples * New section on regression * Online instructors' manual containing solutions to all exercises <advanced undergraduate="" and="" graduate="" students="" in="" computer="" science,="" engineering,="" other="" natural="" social="" sciences="" with="" only="" a="" basic="" background="" calculus="" will="" benefit="" from="" this="" introductory="" text="" balancing="" theory="" applications.advanced="" applications. <advanced undergraduate="" and="" graduate="" students="" in="" computer="" science,="" engineering,="" other="" natural="" social="" sciences="" with="" only="" a="" basic="" background="" calculus="" will="" benefit="" from="" this="" introductory="" text="" balancing="" theory="" applications.review="" of="" the="" first="" edition: This textbook is a classical and well-written introduction to probability theory and statistics... the book is written 'for an audience such as computer science students, whose mathematical background is not very strong and who do not need the detail and mathematical depth of similar books written for mathematics or statistics majors.' ... Each new concept is clearly explained and is followed by many detailed examples... numerous examples of calculations are given and proofs are well-detailed." (Sophie Lemaire, Mathematical Reviews, Issue 2008 m).

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