A Modern Introduction to Probability and Statistics - F.M. Dekking, C. Kraaikamp, H.P. Lopuhaä, L.E. Meester

A Modern Introduction to Probability and Statistics

Understanding Why and How
Buch | Softcover
488 Seiten
2010 | Softcover reprint of hardcover 1st ed. 2005
Springer London Ltd (Verlag)
978-1-84996-952-9 (ISBN)
40,65 inkl. MwSt
Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to modern methods such as the bootstrap.
Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. The strength of this book is that it readdresses these shortcomings; by using examples, often from real life and using real data, the authors show how the fundamentals of probabilistic and statistical theories arise intuitively. 

A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to students. In addition there are over 350 exercises, half of which have answers, of which half have full solutions. A website gives access to the data files used in the text, and, for instructors, the remaining solutions. The only pre-requisite is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to modern methods such as the bootstrap.

Michel Dekking, Cor Kraaikamp, Rik Lopuhaä and Ludolf Meester are professors in the Department of Applied Mathematics at TU Delft, The Netherlands. The material in this book has been successfully taught there for several years, and at the University of Leiden, The Netherlands, and Wesleyan University, USA, since 2003.

Why probability and statistics?.- Outcomes, events, and probability.- Conditional probability and independence.- Discrete random variables.- Continuous random variables.- Simulation.- Expectation and variance.- Computations with random variables.- Joint distributions and independence.- Covariance and correlation.- More computations with more random variables.- The Poisson process.- The law of large numbers.- The central limit theorem.- Exploratory data analysis: graphical summaries.- Exploratory data analysis: numerical summaries.- Basic statistical models.- The bootstrap.- Unbiased estimators.- Efficiency and mean squared error.- Maximum likelihood.- The method of least squares.- Confidence intervals for the mean.- More on confidence intervals.- Testing hypotheses: essentials.- Testing hypotheses: elaboration.- The t-test.- Comparing two samples.

Reihe/Serie Springer Texts in Statistics
Springer Texts in Statistics
Zusatzinfo 120 Illustrations, black and white; XVI, 488 p. 120 illus.
Verlagsort England
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Weitere Themen CAD-Programme
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Naturwissenschaften
ISBN-10 1-84996-952-3 / 1849969523
ISBN-13 978-1-84996-952-9 / 9781849969529
Zustand Neuware
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