Introduction; How to use statistics; Types of data and types of test; Tools of the trade; Single sample tests: is my sample representative or biased?; Two-sample tests for counts in categories data; Two-sample tests for individual measurements; More than 2 samples: are these 3 or more samples different?; Looking at relationships; 10 Conclusions; Appendices.
Danny McCarroll completed a Geography degree at the University of Sheffield in 1983 and a PhD, on Little Ice Age fluctuations of Norwegian glaciers, at Swansea University in 1986. He later worked for a few years in the Universities of Cardiff and Southampton before returning to Swansea, where he has sincereceived awards for excellence in both teaching and research as well as a Personal Chair. His research interests include geomorphology, reconstructing Quaternary environments and high resolution climate reconstruction, particularly using tree rings. He coordinated the European Union funded ‘Millennium’ project which brought together an interdisciplinary team of more than 100 scientists from 40 universities to reconstruct the climate of Europe over the last one thousand years. He has more than 100 publications in international journals.
"This is an unusual and exceptional book! It is designed for
geography students who want to carry out statistical tests. It is
not for teachers or lecturers, and certainly not for practising
statisticians. It is for budding geographers who have interesting
data, collected as part of, say, an undergraduate (or even
postgraduate) project, who need to derive wider meaning from their
results and give their study its due significance. In order to
achieve this aim it is written in a most engaging fashion, directed
at the student colleague, and is designed around the experiments
that the students are likely to encounter in their undergraduate
course. The book is functional throughout. It starts with the
geographical question (i.e. when is the statistical test useful?),
and then takes the student through the rationale, and the process
of how to carry out the test. Functionality persists, and the
student is directed how to carry out the test in a variety of ways:
manually, with a range of calculators, or with the appropriate or
convenient statistical package such as SPSS. To wrap up each
method, the book gives worked examples, of interest to both
physical and human Geographers.
Because Geographers deal with complex problems that are unlikely to
yield appropriate distributions with sound, probabilistic
assumptions, this book is focussed on non-parametric tests and
concentrates on issues such as the inevitably unsuitable sample
size, or complex and maybe extreme distributions. With this in
mind, Professor Danny McCarroll takes his student ‘colleagues’
through the basics and reality of what is needed to do their work.
In so doing, the book introduces them to hypotheses, probability,
data and distributions that underpin their experiment and leads
them through the practicalities of deriving their statistical
implications. The book has even included a series of spreadsheets,
accessible through a hyperlink that can be used to input data and
carry out the statistical test without need to use the usual
specialised software. With this structure, the book takes the user
through, for instance: Chi-Square Tests, Kolmogorov-Smirnov Tests,
Mann-Whitney U-Test, Siegel-Tukey Test and correlation with, for
instance, Spearman’s Rank and Regression Analysis. Retaining its
practicality to the end, the book concludes with tables of Critical
Values for the various tests explained in the preceding text. This
is an outstanding book that will not only bring satisfaction for
coming generations of students, but is likely to greatly increase
the value of early research carried out by geography
undergraduates, wherever they may be."
—Emeritus Professor Jim Rose, Department of Geography, Royal
Holloway, University of London, Visiting Research Associate,
British Geological Survey"Prof. Danny McCarroll is an excellent
geographer with a lot of experience in teaching statistical methods
for geographers. In this book, Prof. McCarroll aims to overcome the
fear of numbers; instead encouraging students to focus on the
geographical problems that interest them and use whatever
statistical tools they need in order to tackle such problems. In
comparison to traditional statistics books, the author focuses
mainly on nonparametric (distribution-free) methods, which are the
most appropriate for geography students to work with due to the
scale of study and the type of data that they encounter. However,
the last chapters do also introduce widely-used parametric methods
such as correlation and regression. Each technique taught in this
book can be adopted and utilized quickly and easily using a range
of tools including free online calculators, free add-ins or using
specialist software (SPSS, R). This is a fantastic book for
students, who can design the sampling scheme to fit the desired
test before collecting data and look for clear guidance on how to
analyse collected data."
—Prof. Jürg Luterbacher, Director Department of Geography, Justus
Liebig University of Giessen, Germany
"This is an unusual and exceptional book! It is designed for
geography students who want to carry out statistical tests. It is
not for teachers or lecturers, and certainly not for practising
statisticians. It is for budding geographers who have interesting
data, collected as part of, say, an undergraduate (or even
postgraduate) project, who need to derive wider meaning from their
results and give their study its due significance. In order to
achieve this aim it is written in a most engaging fashion, directed
at the student colleague, and is designed around the experiments
that the students are likely to encounter in their undergraduate
course. The book is functional throughout. It starts with the
geographical question (i.e. when is the statistical test useful?),
and then takes the student through the rationale, and the process
of how to carry out the test. Functionality persists, and the
student is directed how to carry out the test in a variety of ways:
manually, with a range of calculators, or with the appropriate or
convenient statistical package such as SPSS. To wrap up each
method, the book gives worked examples, of interest to both
physical and human Geographers.
Because Geographers deal with complex problems that are unlikely to
yield appropriate distributions with sound, probabilistic
assumptions, this book is focussed on non-parametric tests and
concentrates on issues such as the inevitably unsuitable sample
size, or complex and maybe extreme distributions. With this in
mind, Professor Danny McCarroll takes his student ‘colleagues’
through the basics and reality of what is needed to do their work.
In so doing, the book introduces them to hypotheses, probability,
data and distributions that underpin their experiment and leads
them through the practicalities of deriving their statistical
implications. The book has even included a series of spreadsheets,
accessible through a hyperlink that can be used to input data and
carry out the statistical test without need to use the usual
specialised software. With this structure, the book takes the user
through, for instance: Chi-Square Tests, Kolmogorov-Smirnov Tests,
Mann-Whitney U-Test, Siegel-Tukey Test and correlation with, for
instance, Spearman’s Rank and Regression Analysis. Retaining its
practicality to the end, the book concludes with tables of Critical
Values for the various tests explained in the preceding text. This
is an outstanding book that will not only bring satisfaction for
coming generations of students, but is likely to greatly increase
the value of early research carried out by geography
undergraduates, wherever they may be."
—Emeritus Professor Jim Rose, Department of Geography, Royal
Holloway, University of London, Visiting Research Associate,
British Geological Survey"Prof. Danny McCarroll is an excellent
geographer with a lot of experience in teaching statistical methods
for geographers. In this book, Prof. McCarroll aims to overcome the
fear of numbers; instead encouraging students to focus on the
geographical problems that interest them and use whatever
statistical tools they need in order to tackle such problems. In
comparison to traditional statistics books, the author focuses
mainly on nonparametric (distribution-free) methods, which are the
most appropriate for geography students to work with due to the
scale of study and the type of data that they encounter. However,
the last chapters do also introduce widely-used parametric methods
such as correlation and regression. Each technique taught in this
book can be adopted and utilized quickly and easily using a range
of tools including free online calculators, free add-ins or using
specialist software (SPSS, R). This is a fantastic book for
students, who can design the sampling scheme to fit the desired
test before collecting data and look for clear guidance on how to
analyse collected data."
—Prof. Jürg Luterbacher, Director Department of Geography, Justus
Liebig University of Giessen, Germany
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