- We will send in 10–14 business days.
/images/books/3633764/9780521317962.jpg)
- Author: Robert Rosenthal
- Publisher: Cambridge University Press
- ISBN-10: 0521317967
- ISBN-13: 9780521317962
- Format: 14 x 21.6 x 0.7 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
This book, first published in 1985, is for those seeking appropriate statistical approaches to research data that is devoted entirely to the topic of contrasts. Contrast analysis permits us to ask more focused questions of our data. In return for a small amount of simple computation, we get greater statistical power, and can make clearer substantive interpretations of the research results. Contrast analysis should be employed in the context of the analysis of variance whenever the numerator degrees of freedom are greater than one (which is probably most of the time). Unfortunately, it is employed relatively rarely by behavioural and social scientists. This book makes it possible for non-mathematical data analysts to avail themselves of contrasts, and thereby simply and efficiently to address the focused questions posed by their theories, hypotheses, and hunches. A wide range of researchers in the behavioural and social sciences, education and business will find this book an invaluable resource.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 23d.09:02:48
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Robert Rosenthal
- Publisher: Cambridge University Press
- ISBN-10: 0521317967
- ISBN-13: 9780521317962
- Format: 14 x 21.6 x 0.7 cm, minkšti viršeliai
- Language: English English
This book, first published in 1985, is for those seeking appropriate statistical approaches to research data that is devoted entirely to the topic of contrasts. Contrast analysis permits us to ask more focused questions of our data. In return for a small amount of simple computation, we get greater statistical power, and can make clearer substantive interpretations of the research results. Contrast analysis should be employed in the context of the analysis of variance whenever the numerator degrees of freedom are greater than one (which is probably most of the time). Unfortunately, it is employed relatively rarely by behavioural and social scientists. This book makes it possible for non-mathematical data analysts to avail themselves of contrasts, and thereby simply and efficiently to address the focused questions posed by their theories, hypotheses, and hunches. A wide range of researchers in the behavioural and social sciences, education and business will find this book an invaluable resource.
Reviews