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Macmillan Higher Education

A Modern Introduction to Probability and Statistics

Understanding Why and How

Author(s):
Publisher:

Springer

Pages: 488
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Recommend to library

AVAILABLE FORMATS

Paperback - 9781849969529

19 October 2010

$59.95

In stock

Ebook - 9781846281686

30 March 2006

$44.99

In stock

Hardcover - 9781852338961

15 June 2005

$59.95

In stock

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...

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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.

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Developed from tried and tested course material, this book provides a self-contained course that is also suitable for self-study

Uses real examples and real data sets that will be familiar to students

Features quick exercises to give direct feedback to the student, and over 350 exercises

Includes an introduction to the bootstrap, a modern method that is often missing in other books

Includes full solutions to half the exercises given in the book; solutions to the rest are provided on an accompanying website

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.
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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.

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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.

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