Statistics for the Behavioral and Social Sciences

This unique book capitalizes on a successful approach of using definitional formulas to emphasize concepts of statistics, rather than rote memorization. This conceptual approach constantly reminds readers of the logic behind what they are learning. Procedures are taught verbally, numerically, and visually, which appeals to a variety of users with different learning styles.Focusing on understanding, the book emphasizes the intuitive, de-emphasizes the mathematical, and explains everything in clear, simple languagewith a large number of practice problems.For those trying to master statistics, as well as reading and understanding research articles.

TO THE INSTRUCTOR The heart of this book was written over a summer in a small apartment near the Place Saint Ferdinand, having been outlined in nearby cafes and on walks in the Bois de Boulogne. It is based on our 40 years of experience teaching, researching, and writing. We believe that this book is as different from the conventional lot of statistics books as Paris is from Calcutta, yet still comfortable and stimulating to the long-suffering community of statistics instructors. The approach embodied in this text has been developed during our combined 40 years of successful teaching--successful not only in the sense that students have consistently rated the course (a statistics course, remember) as a highlight of their undergraduate years, but also in the sense that students come back to us later saying, "I was light-years ahead of my fellow graduate students because of your course," or "Even though I don't do research, your course has really helped me understand statistics that I read about in my field." In this third edition of thisBrief Coursewe have tried to maintain those things about the book that have been especially appreciated, while reworking the text to take into account the feedback we have received, our own experiences, and advances and changes in the field. We have also added new pedagogical features to make the book even more accessible for students. However, before turning to the third edition, we want to reiterate some comments. we made in the first edition about how this book from the beginning has been quite different from other statistics texts. WHAT WE HAVE DONE DIFFERENTLY We continue to do what the best of the newer books are already doing well: emphasizing the intuitive, deemphasizing the mathematical, and explaining everything in direct, simple language. But what we have done differs from these other books in 10 key respects. 1.The definitional formulas are brought to center stagebecause they provide a concise symbolic summary of the logic of each particular procedure. All our explanations, examples, practice problems, and test bank items are based on these definitional formulas. (The amount of data to be processed in our practice problems and test items are reduced appropriately to keep computations manageable.) Why this approach? To date, statistics texts have failed to adjust to technologic reality. What is important is not that the students learn to calculate a correlation coefficient with a large data set--computers can do that for them. What is important is that students work problems in a way that they remain constantly aware of the underlying logic of what they are doing. Consider the population variance--the average of the squared deviations from the mean. This concept is immediately clear from the definitional formula (once the student is used to the symbols) Teaching computational formulas today is an anachronism. Researchers do their statistics on computers now. At the same time, the use of statistical software makes the understanding of the basic principles, as they are symbolically expressed in the definitional formula, more important than ever. Students still need to work lots of problems by hand to learn the material. But they need to work them using the definitional formulas that reinforce the concepts, not using the computational formulas that obscure them. Those formulas once made some sense as time-savers for researchers who had to work with large data sets by hand, but they were always poor teaching tools. (Because some instructors may feel naked without them, we still provide the computational formulas, usually in a brief footnote, at the point in the chapter where they would traditionally have been introduced.) 2.Each procedure is taught both verbally and numerically--and usually visually as well. In fact, when we introduceevery