This website is intended to support Statistical Methods in Psychology, 9th edition by David C. Howell. At the moment (6/5/16) I am working on the 9th edition and stealing stuff from the 8th, so there may be all sorts of stuff here that will be changed or doesn't even belong--e.g. the Logo is the cover of the 8th.) If you are using the 7th or 8th edition, simply change the URLs by changing "methods9" to "methods7" or "methods8" in the address bar.) The website is intended to serve a number of functions. It will provide data that you can use for examples and exercises, answers to exercises (some of them), and other material that you may find useful. In addition, I have tried to incorporate important material on topics that I don't discuss in the text, and helpful hints about where to find useful information on the web.
In this edition I have made much more use of the R programming language. Sometimes I provide the full coding, which includes reading in the data, transforming it to different forms, and doing the analysis. At other times I simply give the code for the specific analysis, assuming that you have already read in the data and done other preparatory work. In these web pages I try to give all of the code that is needed to carry out all of the analyses in the chapter in one file. Sometimes I add other analyses that are not in the chapter but which are relevant to your learning. Each of these pages will be labelled something like "Chapter7RCode.R". In addition, I have a lot more R code that I have written for various occasions, and I am making that available for whatever use you want to make of it. That material will be included in a subdirectory with its own descriptive page. Finally, I have a number of pages that show how to download, install, and use R. I recommend that you go to those pages even if you know a bit about R.
This section contains material on R and its use, as well as R code that provides the output in each chapter and some of which relates to exercises at the end of the chapter. I have broken the material down to a section that covers general R porgramming and then sections for each chapter that cover the R code necessary for that chapter and related material. Many chapter sections will contain supplementary material related to what I cover in the text, and occassionally links to other Web sites that related directly to what I have covered.
Over the years I have assembled a large number of web pages that discuss material that is not covered in the text but go beyond what the text does cover. For example, a standard repeated measures analysis of variance assumes that each subject provides complete data, but there are alternative models of analysis that relax that restriction. Similarly, I discuss the chi-square test at length in the book, but I don't seriously address the question of what you do when your categorical variable is measured on an ordinal scale. I cannot include all of this material in the text because it would probably double its length. So I am making some of that material available via the web. Some of these supplements will be fairly short, and some of them are quite long. I plan to make some of them available as pdf documents because, especially for the long ones, it is easier to print them out rather than work through them on your computer screen. In addition, in the 9th edition I have provided a number of programs (or "code snippets") that will run under the programming environment R. You can get to those and similar pages from this index of supplements.
These files contain the data from most of the examples and exercises in the book. The first line of each file contains the variable names. Instruct your software to treat that line as variable names. In SPSS this is done simply by clicking the appropriate button on the second dialog box. These are ASCII files, and can be imported quite easily into any statistical software. All files are tab-delimited, meaning that a tab character separates adjacent values. I have also included "xxx.sav" files. These are SPSS data files that can be read directly into SPSS. That saves a good bit of time. For R codes, use the "xxxx.dat" files.
I have provided fairly complete answers to odd numbered questions. Where questions ask you to think of an example of something, or verify that your results are the same as the results obtained by software, I generally do not provide answers because there is little to provide. Students often complain that I don't provide answers to the even numbered questions as well, but many instructors do not want all of the answers available. I am just following their requests, which I think are quite reasonable.
Much as I try, assisted by copy editors and proofreaders, errors always find a way of sneaking in. When I find those, or when they are pointed out to me, I add an entry on the errata sheet and try to give credit where it is due.
There is a surprising amount of material available over the internet, and much of it can make the teaching and learning of statistics easier. I have provided links to those websites that I think are particularly useful. However links go bad for reasons completely beyond my control (e.g., the author changes the server on which her pages are posted, or she moves to another university.) As a result, you may get error messages. The easiest thing to do is to try to recover the material by dropping off the last bit of each URL and seeing if that gets you anywhere. Or take the name of the html file and do a search on Google. If I were to change universities, which I won't, I would not rename all of my pages, so searching for the page name would likely get you where you want to go.
A Java applet is a program that can be included in an HTML document and run over the web. There are many of them out there, and they are useful to illustrate important concepts, to serve as statistical calculators for statistical functions, and to simply run analyses. I have links to several of these on the applet page.
A glossary is a list of terms and their definitions. The main one that I point to is one that I wrote, but many other people have written them and I point to theirs as well.
Some time ago Esther Leerkes, now at the University of North Carolina at Greensboro, and I wrote a manual on using SPSS. (Actually Eshter did all the hard stuff, and I made suggestions as she went along.) SPSS is the most commonly available software for statistical analyses, and is easy to use. But we were asked if we could put together an introductory manual. That manual can be found at the above link. It refers to an earlier version of SPSS, but that should make no difference to your use of it.
NOTE!! I have made important changes in this manual on the web site for "Fundamental Statistics for the Behavioral Sciences". The link above will take you there. Do not be confused by the fact that the background has changed.
At some other time I wrote another manual (I no longer recall why) that is a bit more fun to read, but is not as long. This one is called the Shorter Manual for lack of imagination. You can load it at the link above.
I have written a review of basic arithmetic to accompany the Fundamentals book that I wrote. I am always surprised how often people forget some of the most basic material--myself included. You may well know everything in this review, but if you don't, or knew it but don't remember it now, the review should be helpful.
I can't resist adding what is perhaps the best advice I have. If there is something that you don't understand, just remember that "Google is your friend." She certainly is mine. If you don't understand what Fisher's Exact Test is, or you don't like my explanation, go to Google and type in Fisher's Exact Test. I just did that and had 260,000 hits. You can't tell me that there isn't going to be something useful in there.