1st Edition

A Whistle-Stop Tour of Statistics

By Brian S. Everitt Copyright 2012
    212 Pages 51 B/W Illustrations
    by Chapman & Hall

    212 Pages
    by Chapman & Hall

    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.

    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


    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