Overview

Designed to serve as either a graduate-level text or reference book for experimental design, this book should be of use in psychology, education and statistics departments. The book promotes a model comparison perspective rather than the more traditional variance partitioning approach. This approach offers several advantages. Firstly, it better prepares students to understand the logic behind choosing the best technique for a particular design. Secondly, focusing on definitional versus computational formulae allows for a heavier reliance on statistical packages to perform the actual computations, freeing the reader to spend more time on the conceptual understanding versus the number crunching. Finally, the model comparison approach allows for the introduction of more complex topics, generally omitted from other books.

Full Product Details

Author:   Scott E. Maxwell (University of Notre Dame, USA) ,  Harold D. Delaney (University of New Mexico, USA) ,  Ken Kelley
Publisher:   Taylor & Francis Inc
Imprint:   Routledge Academic
Edition:   2nd New edition
Dimensions:   Width: 15.20cm , Height: 6.40cm , Length: 22.90cm
Weight:   2.177kg
ISBN:  

9780805837186

ISBN 10:   0805837183
Pages:   1104
Publication Date:   01 July 2003
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Replaced By:   9781138892286
Format:   Hardback
Publisher's Status:   Out of Stock Indefinitely
Availability:   In Print  
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Reviews

Overall, this is an excellent resource for those designing and analyzing experiments, and for those wishing to consolidate their knowledge of individual designs into a unified conceptual framework. --American Statistician

<p> Overall, this is an excellent resource for those designing and analyzing experiments, and for those wishing to consolidate their knowledge of individual designs into a unified conceptual framework. <br> American Statistician

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