Data Analysis: An Introduction (Quantitative Applications in the Social Sciences)

In 1980, Michael Lewis-Beck published Applied Regression: An Introduction, a remarkably succinct, informative, and above all accessible introduction to regression analysis. I used it selectively as ancillary reading in courses I taught in basic statistics, quantitative research methods, and multiple regression. Students loved it. Finally, a statistics text they could use to help them with material they didn't understand in class or that was not clearly explained in their other readings!Unbeknownst to me, the same author later published another Sage paperback titled Data Analysis: An Introduction. I became aware of this 1995 text only recently, and, after reading it, I realized that the last fifteen of the twenty-three years I taught basic statisitcs before retiring in 2010 would have been much easier for me and much more useful for beginning students if I had learned of the book when it first appeared.As with Lewis-Beck's Applied Regression text, Data Analysis is a tribute to the author's ability to write both succinctly and accessibly about counter-intuitive material that students commonly dread. No reason for dread here, however, because once again Lewis-Beck has written a text that is really useful for beginners who want to use it as supplementary reading for a course or -- wonder of wonders! -- a self-teaching tool. I had long been convinced that the latter objective, producing a reasonably thorough introduction to basic statistics that would serve the interests of those who wanted to teach themselves but who lacked a good deal of mathematical aptitude, was something that would never be written. Lewis-Beck, however, proved me wrong, and he did it in less than eighty pages.If his text has limitations they are manifest in its peculiarly sociologically orientation, meaning that an obligatory introduction to elementary probability theory is not included, and one-way analysis of variance, a tool that is used and misused much too often in some behavioral science disciplines, is not introduced.However, there is much more thorough coverage of regression analysis than is included in all but a few introductory texts. Also, simpler techniques, such as the ubiquitous t test and non-parametric measures of association, including those based on Chi-square, are given their due. Lewis-Beck, however, realizes statistics starts to get interesting when analysts begin applying multiple regression. By the time the reader has worked through the first forty pages of Data Analysis, he or she is ready to make a first foray into material that most instructors save for a second course. If Lewis-Beck's earlier book, Applied Regression, were read as a sequel to Data Analysis, a student could honestly and confidently claim to be pretty well on the way to being a reasonably capable social science statistician.Textbook publishing is a notorious racket. But Lewis-Beck's inexpensive and masterfully written Data Analysis: An Introduction provides a welcome reprieve from the usual rip-off routine.

An excellent primer for basic data analysis. It starts at the beginning of data gathering and discusses basic application of analysis; to include univariate statistics, measures of association, significance testing, simple and multiple regression.I need a reference source to brush the dust off of my college statistics for a project, this book fit the bill for what I required and would recommend it for others. It is not a complex text, rather a booklet which helped me recall the basics of data analysis.

A great tool is one you use often. An invaluable tool is one you use often and never lend to anyone else and you would slap their hand if they even thought about reaching for it. Anyone even thinks about attempting to borrow my copy of this resource and they will draw back a nub! This booklet has proved to be my "go to" handy reference guide for my own research. If you don't have this one on your personal reference shelf you are missing out.

This provides a good, general overview of some aspects of beginning data analysis. It lacks some of the specific applied information that would be helpful in a reference like this. Overall, a more comprehensive "Dummies" guide would be more helpful.

As a Phd student in sociology, I find this booklet indispensable as a quick and easy reference guide to all the basics of social science statistical analysis. After going through more complicated texts such as Lewis-Beck's "Applied Regression: an Introduction" and Berry and Feldman's "Multiple Regression in Practice", I find this small booklet extremely helpful and clear in its explanations of the logic of basic bivariate and multiple regression analysis, as well as significance testing. It is quite useful as a tool to review the basic methods of analysis, and I especially like the list of regression assumptions at the end, all of which we had to memorize and explain for qualifying exams! I would only request a separate section and more detailed explanation of the Chi-square test, complete with application examples.

Book in great condition.

En attente de réception.