A Whistle-Stop Tour of Statistics  book cover
1st Edition

A Whistle-Stop Tour of Statistics

ISBN 9781439877487
Published December 1, 2011 by Chapman & Hall
212 Pages 51 B/W Illustrations

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Book Description

The book is intended as a quick source of reference and as an aide-memoir for students taking A-level, undergraduate or postgraduate statistics courses. It includes numerous examples, helping instructors on such courses by providing their students with small data sets with which to work.

Table of Contents

Some Basics and Describing Data
Population, Samples and Variables
Types of Variables
Tabulating and Graphing data: Frequency Distributions, Histograms and Dotplots
Summarizing Data: Mean, Variance and Range
Comparing Data from Different Groups Using Summary Statistics and Boxplots
Relationship between Two Variables, Scatterplots and Correlation Coefficients
Types of Studies
Suggested Reading

Odds and Odds Ratios
Permutations and Combinations
Conditional Probabilities and Bayes’ Theorem
Random Variables, Probability Distributions and Probability Density Functions
Expected Value and Moments
Moment-Generating Function
Suggested Reading

Point Estimation
Sampling Distribution of the Mean and the Central Limit Theorem
Estimation by the Method of Moments
Estimation by Maximum Likelihood
Choosing Between Estimators
Sampling Distributions: Student’s t, Chi-Square and Fisher’s F
Interval Estimation, Confidence Intervals
Suggested Reading

Inference and Hypotheses
Significance Tests, Type I and Type II Errors, Power and the z-Test
Power and Sample Size
Student’s t-Tests
The Chi-Square Goodness-of-Fit Test
Nonparametric Tests
Testing the Population Correlation Coefficient
Tests on Categorical Variables
The Bootstrap
Significance Tests and Confidence Intervals
Frequentist and Bayesian Inference
Suggested Reading

Analysis of Variance Models
One-Way Analysis of Variance
Factorial Analysis of Variance
Multiple Comparisons, a priori and post hoc Comparisons
Nonparametric Analysis of Variance
Suggested Reading

Linear Regression Models

Simple Linear Regression
Multiple Linear Regression
Selecting a Parsimonious Model
Regression diagnostics
Analysis of variance as regression
Suggested reading

Logistic Regression and the Generalized Linear Model

Odds and odds ratios
Logistic regression
Generalized linear model
Variance function and overdispersion
Diagnostics for GLMs
Suggested reading

Survival Analysis

Survival data and censored observations
Survivor function, log-rank test and hazard function
Proportional hazards and Cox regression
Diagnostics for Cox regression
Suggested reading

Longitudinal Data and Their Analysis

Longitudinal data and some graphics
Summary measure analysis
Linear mixed effects models
Missing data in longitudinal studies
Suggested Reading

Multivariate Data and Their Analysis

Multivariate data
Mean vectors, variances, covariance and correlation matrices
Two multivariate distributions: The multinomial distribution and the multivariate normal distribution
The Wishart distribution
Principal Components Analysis
Suggested reading

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Brian Everitt is Retired from King's College London, UK.


"I think that Everitt has been quite successful. All the standard topics, such as probability, estimation, hypothesis testing, analysis of variance, and regression, are discussed. The discussion is short, to the point, readable, and reliable. In addition, there are the more ‘advanced’ topics of logistic regression, survival analysis, longitudinal data analysis, and multivariate analysis, thus providing the reader with a short introduction to a wide array of the methods in the statistical arsenal without getting bogged down in detail. … a brief, but good, introduction to statistics. … excellent ‘refresher’ for those who have already experienced an introduction to statistics and want a slightly different approach or point of view."
—David Bellhouse, The American Statistician, November 2014

"For an MAA member, this book might serve as a small desktop encyclopedia of statistics … . For someone with the mathematical prerequisites, it can answer questions such as ‘What is logistic regression?’ with a bit more detail than a dictionary of statistics."
—Robert W. Hayden, MAA Reviews, May 2012