03424nam a22005055i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001900153050001600172072001600188072001700204072002300221082001400244100002800258245010500286264004600391300004200437336002600479337002600505338003600531347002400567505019500591520157000786650001702356650002902373650002002402650002502422650002902447650001902476650001602495650001702511650004902528650008902577650005202666650002902718650003302747710003402780773002002814776003602834856004802870978-0-8176-4591-5DE-He21320180115171436.0cr nn 008mamaa100301s2007 xxu| s |||| 0|eng d a97808176459157 a10.1007/978-0-8176-4591-52doi 4aQA273.A1-274.9 4aQA274-274.9 7aPBT2bicssc 7aPBWL2bicssc 7aMAT0290002bisacsh04a519.22231 aSchay, Géza.eauthor.10aIntroduction to Probability with Statistical Applicationsh[electronic resource] /cby Géza Schay. 1aBoston, MA :bBirkhäuser Boston,c2007. aX, 318 p. 44 illus.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda0 aThe Algebra of Events -- Combinatorial Problems -- Probabilities -- Random Variables -- Expectation, Variance, Moments -- Some Special Distributions -- The Elements of Mathematical Statisti. aThis textbook is 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. Main statistical concepts considered are point and interval estimates, hypothesis testing, power function, various statistical tests: z, t, chi-square and Kolmogorov-Smirnov. Key features: * Presents rigorous discussion, with definitions, theorems, and proofs, but aimed at a non-specialist audience; *Avoids linear algebra; * Treats informally the few unavoidable concepts from multivariable calculus, such as double integrals; * Motivates new concepts throughout using examples and brief conceptual discussions; * Develops basic ideas with clear definitions, carefully designed notation and techniques of statistical analysis, along with well-chosen examples, exercises and applications. The book contains enough material for two semesters but, with judicious selection, it can also be used for a one-semester course, either in probability and statistics or in probability alone. .Advanced undergraduate and graduate students in computer science, engineering, and other natural and social sciences with only a basic background in calculus will benefit from this introductory text balancing theory with applications. 0aMathematics. 0aMathematical statistics. 0aMeasure theory. 0aApplied mathematics. 0aEngineering mathematics. 0aProbabilities. 0aStatistics.14aMathematics.24aProbability Theory and Stochastic Processes.24aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.24aProbability and Statistics in Computer Science.24aMeasure and Integration.24aApplications of Mathematics.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z978081764497040uhttp://dx.doi.org/10.1007/978-0-8176-4591-5