This wide-ranging, jargon-free dictionary contains over 2,300 entries on all aspects of statistics, including terms used in computing, mathematics, and probability. It also includes biographical information on over 200 key figures in the field and coverage of statistical journals and societies. While embracing the whole multi-disciplinary spectrum of this complex subject, information is presented in a clear and practical manner. This edition features recommended web links for many entries, accessible via the Dictionary of Statistics website, which provide valuable extra information. This edition features expanded coverage of applied statistics. Entries are generously illustrated with 130 useful figures and diagrams, and include worked examples where applicable. Appendices include a historical calendar of important statistical events, lists of statistical and mathematical notation, and statistical tables.
A dry read but what else to expect with a dictionary of statistics - It does the job well. The inclusion of the short biography of important statisticians was a nice touch.
Oh dear. I had high expectations of this book, but they were immediately shattered. Looking up the definition of standard deviation I find the definition,
The square root of the *variance.
Hmm.. I was expecting a little more than that. But ok, let's check the definition of variance:
It is the square of the *standard deviation.
This is simply not helpful and not what one expects from an Oxford University Press publication. And bear in mind, this fundamental error (which frankly should have been caught in the early editing phase) persists in the third edition!
While it could be a pretty dry book for starters/newcomers in Statistics (after all, no one wants to read from the beginning to the end of a dictionary), it's really convenient to search, understand statistical concepts with clear examples and definition. Highly recommended for people with intermediate/advanced skills in Statistics.
Note: another recommended book with this dictionary is The Art of Statistics: How to Learn from Data from David Spiegelhalter.