You can read it all at once to get a general understanding of this area or you can look at it as you need it as a reference. It was much better than the statistics books I have had as required reading in courses. It's a great resource overall!

You can read it all at once to get a general understanding of this area or you can look at it as you need it as a reference. It's a great resource overall!

You can read it all at once to get a general understanding of this area or you can look at it as you need it as a reference. It was much better than the statistics books I have had as required reading in courses. It's a great resource overall!

The book has several weaknesses that I found require supplementing with other texts. For one, there is no tie-in with major computerized statistical applications like SPSS and SAS nor are there example exercises for students to run and interpret statistical tests for themselves. I have found such exercises to be invaluable in teaching the meaning and uses of multivariate tests. There also should have been a discussion of general issues that cut across the different multivariate tests such as data cleaning, data transformation, the role of correlation matrices and the like and so on. For coverage of these issues, I have found it helpful to use chapters from Tabachnik and Fidel's Using Multivariate Statistics text. Finally, a number of tests, such as survival analysis are not covered in this text, though a second volume by the same authors does cover survival analysis as well as other techniques and should be considered as a companion volume as well.

In sum, this is an excellent and unusually clearly written text that is ideal for non-statistician graduate students in the social sciences. More in-depth analysis of important issues related to multivariate statistics and classroom exercises using statistical computer applications requires augmenting this text with additional readings.