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This title in other editions

A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics)

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A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) Cover

 

Synopses & Reviews

Publisher Comments:

Probability and Statistics are studied by most science students, usually as a second- or third-year course. 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 can show how the fundamentals of probabilistic and statistical theories arise intuitively. It provides a tried and tested, self-contained course, that can also be used for self-study. A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to the students. In addition the book contains over 350 exercises, half of which have answers, of which half have full solutions. A website at www.springeronline.com/1-85233-896-2 gives access to the data files used in the text, and, for instructors, the remaining solutions. The only pre-requisite for the book 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 useful modern methods such as the bootstrap. This will be a key text for undergraduates in Computer Science, Physics, Mathematics, Chemistry, Biology and Business Studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects.

Synopsis:

Suitable for self study

Use real examples and real data sets that will be familiar to the audience

Introduction to the bootstrap is included - this is a modern method missing in many other books

Synopsis:

Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included - this is a modern method missing in many other books

About the Author

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.

Table of Contents

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.- Datasets.- Appendix A: Answers to Selected Exercises.- Appendix B: Solutions to Selected Exercises.- References.- Index.

Product Details

ISBN:
9781849969529
Author:
Dekking, F. M.
Publisher:
Springer
Author:
&
Author:
Meester, L. E.
Author:
ntilde
Author:
Lopuhaä, H.P.
Author:
Kraaikamp, C.
Author:
Hp
Author:
Lopuha, H.P.
Author:
Lopuha
Location:
London
Subject:
Statistics
Subject:
Engineering -- Statistics.
Subject:
Probability
Subject:
Simulation and Bootstrap
Subject:
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Subject:
Appl.Mathematics/Computational Methods of Engineering
Subject:
Probability Theory and Stochastic Processes
Subject:
Mathematics | Probability and Statistics
Subject:
Language, literature and biography
Subject:
mathematics and statistics
Subject:
Engineering mathematics
Subject:
Distribution (Probability theory)
Copyright:
Edition Description:
Softcover reprint of hardcover 1st ed. 2005
Series:
Springer Texts in Statistics
Publication Date:
20101119
Binding:
TRADE PAPER
Language:
English
Pages:
504
Dimensions:
235 x 155 mm 752 gr

Related Subjects


Science and Mathematics » Mathematics » Applied
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) New Trade Paper
0 stars - 0 reviews
$67.25 In Stock
Product details 504 pages Springer - English 9781849969529 Reviews:
"Synopsis" by , Suitable for self study

Use real examples and real data sets that will be familiar to the audience

Introduction to the bootstrap is included - this is a modern method missing in many other books

"Synopsis" by , Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included - this is a modern method missing in many other books
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