Statistical Design For Research


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Statistical Design for Research


Statistical Design for Research

Author: Leslie Kish

language: en

Publisher: John Wiley & Sons

Release Date: 2005-02-25


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The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. This title addresses those basic aspects of research design which are common to many related fields in the social sciences, health sciences, education, and market research. The work presents a unified approach to a common core of problems of statistical design that exists in all these fields, along with basic similarities in practical solutions. Describing many examples and analogies that are 'portable' from application field to application field, Statistical Design for Research deals with designs that are the primary basis of research studies, but are neglected in most statistical textbooks that tend to concentrate on statistical analysis. This text takes a broader, more general and philosophical view of the statistics for the more fundamental aspects of design than do the standard treatments of experimental design. Extensively illustrated and carefully organized into seven chapters and 44 sections, this book can be readily consulted by research workers or graduate students!

Research Design & Statistical Analysis


Research Design & Statistical Analysis

Author: Arnold D. Well

language: en

Publisher: Psychology Press

Release Date: 2003-01-30


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"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover

Statistical Design


Statistical Design

Author: George Casella

language: en

Publisher: Springer Science & Business Media

Release Date: 2008-04-03


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Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. In this book the basic theoretical underpinnings are covered. It describes the principles that drive good designs and good statistics. Design played a key role in agricultural statistics and set down principles of good practice, principles that still apply today. Statistical design is all about understanding where the variance comes from, and making sure that is where the replication is. Indeed, it is probably correct to say that these principles are even more important today.