Danny Mccarroll

Simple Statistical Tests for Geography (eBook, ePUB)

• Format: ePub

Produktbeschreibung

This book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers. The aim is not to teach the mathematics behind statistical tests, but to focus on the logic, so that students can choose the most appropriate tests, apply them in the most convenient way and make sense of the results. Introductory chapters explain how to use statistical methods and then the tests are arranged according to the type of data that they require. Diagrams are used to guide students toward the most appropriate tests. The focus is on nonparametric methods that make very few assumptions and are appropriate for the kinds of data that many students will collect. Parametric methods, including Student's t-tests, correlation and regression are also covered.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 360
• Erscheinungstermin: 3. November 2016
• Englisch
• ISBN-13: 9781498758949
• Artikelnr.: 47139371

Autorenporträt

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 since received 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.

Inhaltsangabe

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.