Skip to content

Experimental Design and Analysis

Best in textbook rentals since 2012!

ISBN-10: 0803938543

ISBN-13: 9780803938540

Edition: 1990

Authors: Steven R. Brown, Lawrence E. Melamed

List price: $42.00
Blue ribbon 30 day, 100% satisfaction guarantee!
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!

Description:

"Brown and Melamed's book is one of the best concise treatments of the design and analysis of experiments that I have seen. The authors begin by showing the significance of variability (variance) for the analysis of experiments, and clearly illustrate the utility of the analysis of variance (ANOVA) model to the analysis of experimental data. They also provide a clear discussion of more advanced topics such as nested, factorial, split-plot, and repeated measures designs. Their book is comprehensive, handles each topic deftly, and should be readily accessible to researchers with a good grounding in basic statistics." --Contemporary Sociology "The book is well written and includes useful…    
Customers also bought

Book details

List price: $42.00
Copyright year: 1990
Publisher: SAGE Publications, Incorporated
Publication date: 8/1/1990
Binding: Paperback
Pages: 96
Size: 5.30" wide x 8.40" long x 0.30" tall
Weight: 0.308
Language: English

Current research centers on the development of neuropsychological diagnostic instruments for determining the visual processing deficits associated with right hemisphere brain lesions. Currently, a multifaceted search task is being employed in an attempt to distinguish parvo from magnocellular processing disorders. A second interest is in the sex differences that exist in the expression of these visual processing disorders and in other areas of neuropsychological assessment. Work also continues on the use of the Kent Perceptual Processing Inventory in neuropsychological assessment of learning disabilities and ADHD.

Introduction and Overview
Variability
Test
Analysis of Variance
Completely Randomized Design
Comparisons and Trends
Treatments by Blocks
Algorithms
Factorial Design
Spilt-Plot and Repeated Measures Designs