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(More customer reviews)Howell's book has been around now for 6 editions - you simply do not get to that stage of publishing a technical book without doing many things very well. I have taught advanced statistics to graduate students and professionals in a variety of programs and settings for over 20 years, and
for an advanced basic course in statistics for graduate students or for knowledgeable professionals, I would not teach from any other text for this level of statistics. If graduate students understood most of the content of this text, they would be better equiped researchers than most currently are for sure. It is true that if this book were to be your first treatment of statistics or if your first course was really not all that thorough or was a long time ago, this text might be difficult for you - but not because the text is poorly done. I also refer this text to graduate students, new Ph.D.s, experienced Ph.D.s who are not statistical experts, and other researchers as a desk reference, and I keep it on my desk and keep a copy in my research lab for my research assistants. Graduate students have always consistently strongly praised the book at the end of the semesters when I have used it. Frankly, I suspect other reviewers of this book who give it low marks have ulterior motives such as steering folks to other specific texts. In this veign, I do not personally know the author, but the author David Howell is a highly respected psychologist with true expertise in statistical methods and who served as chair of his department prior up to his relatively recent retirement at the University of Vermont.
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STATISTICAL METHODS FOR PSYCHOLOGY surveys the statistical techniques commonly used in the behavioral and social sciences, especially psychology and education. This book has two underlying themes that are more or less independent of the statistical hypothesis tests that are the main content of the book. The first theme is the importance of looking at the data before formulating a hypothesis. With this in mind, the author discusses, in detail, plotting data, looking for outliers, and checking assumptions (Graphical displays are used extensively). The second theme is the importance of the relationship between the statistical test to be employed and the theoretical questions being posed by the experiment. To emphasize this relationship, the author uses real examples to help the reader understand the purpose behind the experiment and the predictions made by the theory.
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