# Introduction to Probability with Statistical Applications [electronic resource] / by Géza Schay.

##### By: Schay, Géza [author.]

##### Contributor(s): SpringerLink (Online service)

Material type: TextPublisher: Boston, MA : Birkhäuser Boston, 2007Description: X, 318 p. 44 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780817645915Subject(s): Mathematics | Mathematical statistics | Measure theory | Applied mathematics | Engineering mathematics | Probabilities | Statistics | Mathematics | Probability Theory and Stochastic Processes | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Probability and Statistics in Computer Science | Measure and Integration | Applications of MathematicsAdditional physical formats: Printed edition:: No titleDDC classification: 519.2 LOC classification: QA273.A1-274.9QA274-274.9Online resources: Click here to access onlineItem type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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The Algebra of Events -- Combinatorial Problems -- Probabilities -- Random Variables -- Expectation, Variance, Moments -- Some Special Distributions -- The Elements of Mathematical Statisti.

This 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.

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