It had been a difficult couple of years. I had more life changes than most people have in 30 years, and not the least was that I had moved three times. In the middle of it all, I took multivariate statistics, a graduate course that I didn't have all the prerequisites for. I loved the course, but wow, was it hard. The sheer volume of the work nearly flattened me. Then I had an emotional meltdown right in the middle of the semester project, which was to apply seven multivariate techniques to the data I had collected for my own research.
My professor gave me an "incomplete," bless him, and I had the summer to finish the project. Then I moved again and lost everything -- class notes, textbook, everything.
Then I found this book, and it was all I needed to complete most of the project. Each section describes a statistical procedure clearly, with examples. It is easy to decide whether the technique is appropriate for your data, or, as in my case, how to use your data to try a technique. Then you walk through the technique, step by step, with pictures. The book gives you annotated printouts to help you find the most useful information in what SPSS gives you.
Then, my favorite part -- a sample results section in APA style. If I hadn't had this, I would never have finished by my revised due date, and would have had to repeat the course.
Downside -- it tells you what choices to make as you go through each analysis without fully explaining the options. That's good when you're in a hurry (and I was) but I would love to see these authors make an expanded version to use when I have more time. I would like their help with choosing additional graphs, for instance.
It doesn't help with non-SPSS techniques, of course, and I certainly could have used some help with Structural Equation Modeling. I have since bought Rex Kline's excellent book for that.
If you need to do some heavyweight statistics, you have SPSS, and you find the SPSS help file impenetrable (if you can understand it, you don't need it), then this book is for you. It's worth its weight in gold, and it's heavy.