Table Of ContentTranslating
Statistics to
Make Decisions
A Guide for the Non-Statistician
―
Victoria Cox
TRANSLATING STATISTICS
TO MAKE DECISIONS
A GUIDE FOR THE NON-STATISTICIAN
Victoria Cox
Translating Statistics to Make Decisions: A Guide for the Non-Statistician
Victoria Cox
Salisbury, United Kingdom
ISBN-13 (pbk): 978-1-4842-2255-3 ISBN-13 (electronic): 978-1-4842-2256-0
DOI 10.1007/978-1-4842-2256-0
Library of Congress Control Number: 2017934647
Copyright © 2017 by Victoria Cox
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Contents
About the Author ix
About the Technical Reviewer xi
Introduction xiii
Chapter 1: Design of Experiments 1
Chapter 2: Data Collection 33
Chapter 3: Exploratory Data Analysis 47
Chapter 4: Descriptive Statistics 75
Chapter 5: Measuring Uncertainty 103
Chapter 6: Hypothesis Testing 125
Chapter 7: Statistical Modeling 161
Chapter 8: Multivariate Analysis 241
Chapter 9: Graphs 271
Chapter 10: Translation and Communication 307
Index 319
About the Author
Victoria Cox is a senior statistician at the United Kingdom’s Defence Science
and Technology Laboratory (Dstl). There she advises internal teams and
external organizations, both nationally and internationally, on the experimental
design of statistical studies and the application of the methods of statistical
analysis to a wide variety of practical problems. She teaches statistical courses
to non-statistician scientists, technologists, analysts, managers, and executives.
Cox took her degree in mathematics from the University of Sheffield and
studied at l’Ecole Nationale de la Statistique et de l’Analyse de l’Information
(ENSAI).
About the Technical
Reviewer
Alison Berry has an honors degree in Statistics from the University of
Reading and is accredited as a Chartered Statistician by the Royal Statistical
Society. She has worked in the United Kingdom’s Ministry of Defence for 20
years as a senior statistician and an analyst.
Introduction
This introduction will give an overview as to what the book is about, who the
author—me, is, how the book is laid out, what you should learn by its end, and
more information about R - if you choose to use it.
What the Book Is About
This book is designed to highlight typical misconceptions non-statistics users
can have, to show common pitfalls that (new) statisticians and those dipping
their toes in the water can fall into, and to suggest solutions to correct and
avoid them.
Although the book is written from my viewpoint and therefore the statistician’s
viewpoint, the emphasis is on translating the output correctly to aid evidence-
based business decision making.
Statistics can seem like a tricky subject at first, but once you can get your mind
around the basic ideas, the rest will come easily. The general process, which we
will walk through in the book, has a clear order from designing an experiment,
through analysis, to reporting the results. However once understanding has
been achieved in certain terms and ideas, such as confidence intervals,
p-values, and so forth, this can make the more complicated methods simpler.
For example, some of the more complex models are just extensions of simple
hypothesis tests in terms of the output and the results you would pull out.
Once immersed in the world of statistics it is very easy to get lost in the
language - however this book is written with the non-statistician customer in
mind. Don’t worry, there won’t be any complicated algebra or proofs included
as there are plenty of other texts for that purpose.
The key to effective decision making is to make full use of all available
relevant data. However if this is not in an accessible language then sometimes
important information can be ignored. This is where being able to translate
the statistical jargon into English is vital, and this can be a whole new skill in
itself. Throughout the book we discuss how to make reporting the results an
easy and understandable task.
xiv Introduction
Each section contains advice about how to proceed with each type of data,
method, and so forth along with potential pitfalls and misconceptions related
to the topic. There is dummy example data provided, however the case studies
they refer to in the majority of cases are real scenarios. R code is provided to
help you run through the examples should you wish, but it is not necessary
that you have previous knowledge of R. The text is written in such a way that
the example code is extra information to that which is already provided.
The main aim throughout is to make sure the right methods are being used
on the right data, so the right output is produced and the right conclusions
are translated to the customer. We want to avoid ending up giving wrong or
misleading conclusions to the customer due to something going awry at one
of the many points throughout the design and analysis process.
Who Is the Author?
I am a senior statistician, so day to day I am absorbed in consulting on statistics,
creating experimental designs, and conducting analysis. However I work for a
defense organization where most of my customers and colleagues have never
done statistics, or have done very little, so it is my job to help them understand
the messages in their data. A lot of statistical output can be produced, but it
would be unproductive for them to see it all. The challenging task is to pick
out the important information, which should include main assumptions and
“negative” results, and then condense it to a manageable size.
My day job involves working with military, industry, academic, and government
colleagues and customers. Part of a statistician’s task is to learn about the
subject matter so the results can be translated accordingly, which is why I
made the choice of having a wide variety of case studies in the book.
I have never been a fancy wordsmith, but that has actually been extremely
beneficial in being able to simplify statistical terms to those who haven’t
studied the subject. This also has helped with the internal Introduction to
Statistics course I run for those who want to improve their statistical ability,
as I’ve found I can teach the course without people being completely baffled
by the, quite frankly, backward statistics language.
How Is the Book Laid Out?
Presumably you will have read the contents page, but I will go into a bit more
detail about each of the sections. At this point there may be terms you are
unfamiliar with, don’t worry, these will be explained in the relevant chapters.
There will be examples and figures included throughout the book; many of
the examples will be run in R, but for those not wishing to use R there are
sections translating the output at each stage with summaries at the ends.
