Discovering Statistics Using SAS
Many social science students (and researchers for that matter) despise statistics. For one thing, most of us have a non-mathematical background, which makes understanding complex statistical equations very difficult. Nevertheless, the evil goat-warriors of Satan force our non-mathematical brains to apply themselves to what is, essentially, the very complex task of becoming a statistics expert. The end result, as you might expect, can be quite messy. The one weapon that we have is the computer, which allows us to neatly circumvent the considerable disability that is not understanding mathematics. The computer to a goat-warrior of Satan is like catnip to a cat: it makes them rub their heads along the ground and purr and dribble ceaselessly. The only downside of the computer is that it makes it really easy to make a complete idiot of yourself if you don’t really understand what you’re doing. Hence this book. Well, actually, hence a book called ‘Discovering Statistics Using SPSS’.
I wrote ‘Discovering statistics using SPSS’ just as I was finishing off my Ph.D. in Psychology. The advent of computer programs like SAS, SPSS, R and the like provided the unique opportunity to teach statistics at a conceptual level without getting too bogged down in equations. However, some books based on statistical computer packages concentrate on ‘doing the test’ at the expense of theory. Using a computer without any statistical knowledge at all can be a dangerous thing. My main aim, therefore, was to write a book that attempted to strike a good balance between theory and practice: I want to use the computer as a tool for teaching statistical concepts in the hope that you will gain a better understanding of both theory and practice. If you want theory and you like equations then there are certainly better books: Howell (2006), Stevens (2002) and Tabachnick and Fidell (2007) are peerless as far as I am concerned and have taught me (and continue to teach me) more about statistics than you could possibly imagine. (I have an ambition to be cited in one of these books but I don’t think that will ever happen.) However, if you want a book that incorporates digital rectal stimulation then you have just spent your money wisely. (I should probably clarify that the stimulation is in the context of an example, you will not find any devices attached to the inside cover for you to stimulate your rectum while you read. Please feel free to get your own device if you think it will help you to learn.)
A second, not in any way ridiculously ambitious, aim was to make this the only statistics textbook that anyone ever needs to buy. As such, it’s a book that I hope will become your friend from first year right through to your professorship. I’ve tried, therefore, to write a book that can be read at several levels (see the next section for more guidance). There are chapters for first-year undergraduates (1, 2, 3, 4, 5, 6, 9 and 15), chapters for second-year undergraduates (5, 7, 10, 11, 12, 13 and 14) and chapters on more advanced topics that postgraduates might use (8, 16, 17, 18 and 19). All of these chapters should be accessible to everyone, and I hope to achieve this by flagging the level of each section (see the next section).
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