Statistics in a Nutshell
A Desktop Quick Reference
Publisher: O'Reilly Media
Final Release Date: July 2008
Pages: 480

Need to learn statistics as part of your job, or want some help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts.

You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis.

Organized into four distinct sections, Statistics in a Nutshell offers you:

    Introductory material:
  • Different ways to think about statistics
  • Basic concepts of measurement and probability theory
  • Data management for statistical analysis
  • Research design and experimental design
  • How to critique statistics presented by others


  • Basic inferential statistics:
  • Basic concepts of inferential statistics
  • The concept of correlation, when it is and is not an appropriate measure of association
  • Dichotomous and categorical data
  • The distinction between parametric and nonparametric statistics


  • Advanced inferential techniques:
  • The General Linear Model
  • Analysis of Variance (ANOVA) and MANOVA
  • Multiple linear regression


  • Specialized techniques:
  • Business and quality improvement statistics
  • Medical and public health statistics
  • Educational and psychological statistics

Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to over-emphasize calculation without teaching you when and how to apply different statistical tests.

With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.

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oreillyStatistics in a Nutshell
 
2.4

(based on 8 reviews)

Ratings Distribution

  • 5 Stars

     

    (2)

  • 4 Stars

     

    (0)

  • 3 Stars

     

    (1)

  • 2 Stars

     

    (1)

  • 1 Stars

     

    (4)

20%

of respondents would recommend this to a friend.

Pros

    Cons

    • Too many errors (5)

    Best Uses

      Reviewed by 8 customers

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      Displaying reviews 1-8

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      (3 of 3 customers found this review helpful)

       
      1.0

      -2 is positive?

      By --

      from West Seneca, NY

      About Me Developer

      Verified Reviewer

      Pros

        Cons

        • Too many errors

        Best Uses

        • Intermediate

        Comments about oreilly Statistics in a Nutshell:

        Wanting to firm up my knowledge of statistics, I picked up
        a book titled "Statistics in a Nutshell: A Desktop Quick Reference"
        by Sarah Boslaugh and Paul Andrew Watters
        (ISBN: 978-0-596-51049-7).

        I jumped right to Chapter 9: The Correlation Coefficient
        to check on the exact definition of this concept.
        On page 171 is the explanation
        ==QUOTE==
        In the general form of the model y = +/-ax +/- b:
        * y is the dependent variable
        * +/-a is the _slope_ (i.e., where the value of y when x = 0);
        -a indicates a negative association; +a indicates a positive association
        * x is the independent variable
        * +/-b is the _intercept_ of the straight line
        ==UNQUOTE==
        That parenthesized clause lacks a verb "where the value of y [is]",
        and it describes not the slope but the intercept;
        it should appear after the words "straight line".

        And on the very same and the next page is the wording
        ==QUOTE==
        -- the first values plotted are (1, -2), (2, -4), and (3, -6).
        The model for this relationship is y = -2x, which is
        multiplicative in nature. Using the linear model,
        a = -2, which is positive, so the relationship is positive.
        Again, b = 0, since the intercept is the origin (0,0).
        ==UNQUOTE==
        Huh? -2 is positive? And in these two quotes, the
        word "intercept" is being used in two mutually incompatible
        ways: in the first quote, the intercept is a number;
        in the second quote, the intercept is a point on the xy plane.
        Moreover, the word "intercept" is not listed in the index (p. 447).

        So here's a nice statistics problem for ya:
        Having found four obvious errors in a random sample
        of two pages of a 453-page book, what degree of
        confidence should we assign to whatever this book says
        about a given topic?

        What is going on here? Is this some kind of joke?
        Did no editor read the text of this college textbook?

        Page xx of this book has a section titled
        "We'd Like to Hear from You", which says,
        "To comment or ask technical questions about this book,
        send email to: bookquestions@oreilly.com ".
        It also says:
        "We have a web page for this book, where we list errata,
        examples, and any additional information. You can access
        this page at:
        http://www.oreilly.com/catalog/9780596510497 "
        (Get it? That number is the book's ISBN number).
        But if you go there, you instead are taken to
        http://shop.oreilly.com/product/9780596510497.do ,
        which, as far as I can see, lists no errata at all for
        a book that was released over four years ago, in July 2008.

        I wanted to send a copy of this note to the two authors too,
        but I can't find their e-mail address in the book or on the
        O'Reilly page. Let's try an online search...
        http://www.ofcs.org/sarah-boslaugh/
        says that Sarah Boslaugh has given up biostatistics in
        favor of being a movie critic(!).
        And a search on Paul Andrew Watters leads to
        http://dblp.uni-trier.de/pers/hd/w/Watters:Paul_Andrew.html ,
        which is a page of the Universitaet Trier, the town
        of a cousin of my mother's (kleine Welt! Hallo, Porta Nigra!).
        But still I can't find the authors' e-mail addresses.
        If anybody can find them, feel free to send them this note.

        The surnames Boslaugh and Watters are interesting too.
        I can't figure out whether to say "BOSS laff" or "BOSS law",
        or whether "Watters" rhymes with "waters" or with "matters".

        -- Mark Spahn (West Seneca, NY)

        (0 of 2 customers found this review helpful)

         
        5.0

        Typo?

        By paul

        from Honolulu

        About Me Educator

        Pros

        • Concise
        • Easy to understand
        • Helpful examples

        Cons

        • Too basic

        Best Uses

        • Novice
        • Student

        Comments about oreilly Statistics in a Nutshell:

        Go to Page and 157, first paragraph. The population mean is 1.708<mu<2.292. Is this right?

        (3 of 3 customers found this review helpful)

         
        3.0

        Errors Make Reading Difficult

        By Stats Hungry

        from Northbrook, IL

        Pros

          Cons

          • Too many errors

          Best Uses

            Comments about oreilly Statistics in a Nutshell:

            The book makes it difficult to grasp new concepts because of the errors. Reading requires two-hands: one for the highlighter and the other for the Errata sheet. The Errata sheet has 12 pages, so you can't fold it and slip it into the book. Additionally, if you print the Errata sheet, the formatting is messed up. Text are on top of other text, making it unreadable in certain spots.

            (4 of 4 customers found this review helpful)

             
            1.0

            Agree, not a Nutshell and Errors!

            By DrDave

            from Charlotte

            Pros

              Cons

              • Too many errors

              Best Uses

                Comments about oreilly Statistics in a Nutshell:

                Disappointing, does not reflect well on O'Reilly. I'll have to recycle it - I wouldn't want someone to pick it up and try to learn basic statistics from it!

                (19 of 20 customers found this review helpful)

                 
                1.0

                Lots of Errors

                By Epidemiology Background

                from Minnesota

                About Me Epidemiologist

                Pros

                  Cons

                  • Binomial distribution
                  • Too many errors
                  • T-test

                  Best Uses

                    Comments about oreilly Statistics in a Nutshell:

                    I've been reading through the book as a quick review of basic statistics while trying to learn some statistics computing packages. So far, the book has been riddled with computational errors, basic errors for variable definitions, and figures that say they will show something they don't. For example, trying to define the binomial distribution, the authors confuse the variables for trials and successes in a Bernoulli process. The authors do not explain how to really calculate a t-test. For example, the authors provide a value for the mean in an example of the t-test, and then use a different mean later in the example for calculating confidence intervals without actually defining what numbers should be going into the confidence interval calculation. Not at all proof read, as another reviewer has stated.

                    Without a reasonable strong statistics background for a masters degree in epidemiology, I would be left confused by a great deal of the explanations in this book. Not a tried and true reference...

                    (17 of 18 customers found this review helpful)

                     
                    2.0

                    NOT the Stats book I was hoping for

                    By drumlin

                    from North Carolina

                    About Me Educator, Maker, Scientist

                    Verified Reviewer

                    Pros

                      Cons

                      • Not comprehensive enough
                      • Too many errors

                      Best Uses

                        Comments about oreilly Statistics in a Nutshell:

                        I bought this hoping for the one 'magic' stats book that explained statistics in plain english. Unfortunately this is not the one. I concur that this book is riddled with errors, and it's written not so much as a reference book, but as an explanatory text. Very few worked examples. Bummer.

                        (20 of 21 customers found this review helpful)

                         
                        1.0

                        Not a Nutshell" book and riddled with errors"

                        By dyoung

                        from Undisclosed

                        Comments about oreilly Statistics in a Nutshell:

                        I had high hopes for this book. The world really needs a reference guide for those of us who have had exposure to statistics in college, but often don't remember which tool to turn to (t-test? F-test? Chi-square? a non-parametric test? I don't remember which to use when!). It would have been perfect to provide handy reference tables for which tools to look into in various circumstances, along with the assumptions that must be met to use that tool and a reference to a page number where the tool is briefly explained with some examples. I would have been happy to use this to get me started and then google for more detailed information.

                        This isn't that book. There are no handy reference tables (of any sort) in this book.

                        Despite the "Nutshell" title, this book is written as if it is a linear, beginner primer on statistics.

                        I could be OK with that if it were a good beginner primer on statistics. Instead, the authors seem to assume that "Nutshell" in the title is a license to cut corners in their explanations, leaving the beginning reader confused.

                        The worst part is that the book is riddled with errors. If you're trying to follow the examples and learn from them, you're never sure if you just don't understand or if this is yet another typo/error. Chapter 8 on t-test is so full of computation errors and typos that I doubt it was ever proof-read.

                        (4 of 14 customers found this review helpful)

                         
                        5.0

                        Excellent stat reference book

                        By ueberhund

                        from Undisclosed

                        Comments about oreilly Statistics in a Nutshell:

                        While many of the "Nutshell" books assume you already know the subject and simply need a reference book, Statistics In A Nutshell takes a decidedly different approach. While this book assumes you understand basic math concepts, it does not assume you have any prior background in statistics. It then proceeds to cover nearly every fundamental concept taught during an introductory statistics course.

                        While many introductory statistics courses go through basic descriptive statistics and move through more advanced concepts like ANOVA or liner regression, I found that this book also covered such concepts as non-parametric tests, design of experiments, and the general linear model. Certainly, these concepts are not covered in as much depth as say a college-level courses dedicated to non-parametric statistics. However, the concepts are there, and the authors provide enough information to make the discussion valuable.

                        The last few sections of the book discuss the use of statistics in a variety of professions, including manufacturing, business, medical, and education fields. Individuals who may not feel comfortable with their math skills can take comfort in the fact that the book provides a section on basic math skills, however, those who may be mathematically challenged may argue with the term "basic".

                        All in all, I think this is an excellent book for individuals who are looking to implement the scientific method and statistics in their business. The author provides sound explanations of the concepts and plenty of figures and tables to explain difficult concepts. I'd highly recommend this book for the reader who is not afraid of a little math and wants to understand statistics and statistical concepts.

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