Russel-Research-Method-in-Anthropology

Preface
xi
21, you will be able to use basic statistics to describe your data and you’ll be
able to take your data to a professional statistical consultant and understand
what she or he suggests.
Chapter 19 deals with univariate statistics—that is, statistics that describe a
single variable, without making any comparisons among variables. Chapters
20 and 21 are discussions of bivariate and multivariate statistics that describe
relationships among variables and let you test hypotheses about what causes
what.
I don’t provide exercises at the end of chapters. Instead, throughout the
book, you’ll find dozens of examples of real research that you can replicate.
One of the best ways to learn about research is to repeat someone else’s successful
project. The best thing about replicating previous research is that whatever
you find out has to be significant. Whether you corroborate or falsify
someone else’s findings, you’ve made a serious contribution to the store of
knowledge. If you repeat any of the research projects described in this book,
write and tell me about what you found.
What’s New in This Edition?
New references have been added throughout the book (the bibliography is
about 50% larger than in the last edition) to point students to the literature on
the hundreds of methods and techniques covered.
In chapter 1, I’ve added information on the social science origins of probability
theory. I’ve added several examples of interesting social science variables
and units of analysis to chapter 2 and have spelled out the ecological
fallacy in a bit more detail. I’ve added examples (Dordick, Price, Sugita,
Edgerton) and have updated some examples in table 3.1. Chapter 4 has been
thoroughly updated, including tips on how to search online databases. Some
examples of natural experiments were added to chapter 5. In chapter 6, I added
examples (Laurent, Miller, Oyuela-Cacedo), and there’s a new example on
combining probability and nonprobability samples. In chapter 7, I updated the
example for the central limit theorem.
Chapter 8, on nonprobability sampling and selecting informants, is much
expanded, with more examples and additional coverage of chain referral methods
(including snowball sampling), case control sampling, and using consensus
analysis to select domain specific informants. In chapter 9, on unstructured
and semistructured interviewing, the sections on recording equipment and on
voice recognition software (VRS) have been expanded. This may be the last