Multiple Regression: A Primer (Research Methods and Statistics)

This easy-to-understand text is useful as preliminary or ancillary reading in a first course in regression analysis. For students having trouble with Gujarati, Wooldridge, Chatterjee and Hadi, or other standard introductory texts, the material contained in this brief account will almost certainly be helpful.Allison's text provides the sort of overview that enables students to place detailed treatments of specific topics in a coherent context. This helps them understand just what they are trying to accomplish with all the tests, correctives, and relatively advanced analytical procedures that make up the bulk of usual textbooks on this widely used and increasingly technical topic.The underlying logic of regression analysis can be understood by readers who lack what is sometimes referred to as mathematical maturity. This is especially pertinent with regard to multiple regression and the crucial issue of statistical control. The author does a fine job of making this about as clear as it can be.

This book provides a good conceptual explanation of regression. Mind you, it is still very dry, but that's the nature of the subject matter.The book, unfortunately, uses minimal examples to explain regression and has little to no practice problems. As with all mathematical subjects, I believe the key to understanding is practice and application of the mathematical principles to problems. In that regard, the book left much wanting.To be fair, the author uses few key examples to explain and apply regression principles. But I felt there needed to be much more.This is a paperback and a short book. It is rather skimpy. For that, I felt the price of the book was rather high. But then again, books on regression analysis aren't exactly best-sellers and I suppose the price needs to be high to make-up for the lack of demand. Still, I can't say the book was worth the price.If you want to understand regression better, then this is a worthwhile book. If you want to supplement your good understanding of regression, then I recommend this book. If you want a book that will allow you to understand AND learn regression through practice problems, then look elsewhere.

This book positions itself as a gentler introduction to multiple regression which is both good and bad. The prose makes it easy to read, but in the end this book should have used formatting that better outlines the step-by-step approach needed in multiple regression problems. I swear I'm not kidding here; they do examples where they insert math steps in the middle of sentences in the middle of paragraphs. That doesn't help anyone. Put the examples in clearly outlined boxes like a "real" textbook and outline the steps. The author has written a really decent book - but in the next edition he shouldn't be shy about giving readers enough step-by-step outlines to try some problems. He seems to back off of that for fear of seeming too "technical." Don't worry about it - readers know how to skip ahead. We've been doing it for years.

I had a data science class last semester and my professor assigned this book for the class. To be honest, I had a fear of math. However, this book is amazing. Very easy to understand regression.

I hesitated when I saw "undergraduate" since it is actually listed as a textbook in my graduate class. I ended up buying anyway, and I really like it! For me, the first half is a quick over view and the second half is a nice summary of what I have learned before and quick making-up of something I was not aware of. After all, I would say it is a keeper.

This book is easy to read and follow. I would recommend this for anyone who is diving into the world of research and trying to better understand multiple regression.

I liked this stats book a little better than some of the other books I've had to buy but just barely. It's still a stats book and there won't be anything that can make you really get into stats unless you just love that type of stuff.

Of all the regression books I was assigned, this one made the process easy to understand. By using real-world examples and descriptive words, readers are able to digest the information easily.

This is by far the best basic introduction to multiple regression that I have come across. For those who find MR daunting, I cannot recommend this book too highly.

I ordered the Kindle version because I like being able to search up terms easily. Unfortunately, there are several instances where part of a sentence is missing, or the text explaining an equation is missing numbers. For example: "Regardless of the correlation, the point where the two lines intersect is always ." (pg. 112). Or, "The hand calculator doesn’t know to do this, but we can correct it by multiplying its standard error by . When we multiply 207 by we get exactly the right standard error of 210." (pg. 110). The missing text happens quite a bit throughout the Kindle version, which means you have to fill in the blanks by getting on the internet, and that slows the learning process down.When the sentences ARE complete, the text is written in a way that's easier to understand than other statistics books I've had to read.