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Primer in Data Reduction – An Introductory Statistics Textbook

Autor ASC Ehrenberg
en Limba Engleză Paperback – 22 iun 1982
This is an introductory text in statistics for those who are not specialists in the subject. It makes the subject more relevant for students who have to use statistics as part of their other studies. It avoids mathematics without oversimplifying, emphasizing numeracy and relevance. It not only describes traditional statistical methods but deals with their limitations and discusses alternatives.

The approach derives from the Author's earlier successful book on Data Reduction adapted here for classroom use. It covers the basic topics of a statistics course: averages and measures of scatter, frequency distributions and probability, sampling and statistical inference, relationships (including correlation regression, lawlike relationships, and an introduction to multivariate methods), the communication of data, and the design and interpretation of scientific studies. A teachers' guide is available from the publishers.

"Data Reduction is a very innovative different kind of basic statistical book. I believe our discipline and the disciplines of those whose students we teach would be much better off if we based our first and second courses on Ehrenberg's book rather than on any book of which I am aware."
--Brian L. Joiner, review of Data Reduction, JASA, September 1982

"It is rare for a text-book, particularly an elementary one, to appeal to the established practitioner many of the tenets contained in this excellent, clear, short and readable work, make one regret it was not available sooner."
--The Business Economist, Spring 1983

"If you have time to read just one book on basic statistics, The Primer should be it.
--Chuck Chakrapani, PMRS Journal, Toronto, Nov 1982

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Specificații

ISBN-13: 9780471101352
ISBN-10: 0471101354
Pagini: 324
Dimensiuni: 152 x 229 x 18 mm
Greutate: 0.48 kg
Editura: Wiley
Locul publicării:Chichester, United Kingdom

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Descriere

A concise, easy to understand introduction that emphasizes the relevance of statistics to real world problems. Describes traditional statistical methods, their uses and limitations, and explains how to reduce numerical data to statistical summaries, how to interpret the results, and how to present the data clearly.