# Statistical Concepts: A Second Course

## Synopsis

Richard Lomax provides a conceptual, intuitive approach to the subject that requires only a rudimentary knowledge of basic algebra. Concepts are clearly stated and supported by real-life examples. Statistical Concepts features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwise regression. The book features a thorough and current discussion of assumptions, the effects of their violations, and how to deal with their violation. This text is designed for a second or intermediate course in statistics for students in education and the behavioral sciences. It includes a number of regression and analysis of variance models, all subsumed under the general linear model (GLM). A prerequisite of introductory statistics (descriptive statistics through t-tests) is assumed.

## Excerpt

I know, I know! I've heard it a million times before. When you hear someone at a party mention the word statistics or statistician, you probably say "I hate statistics" and turn the other cheek. in the more than 20 years I have been in the field of statistics, I can only recall four or five times when someone did not have that reaction. Enough is enough. With the help of this text, the "I hate statistics" slogan will become a distant figment of your imagination.

As the title suggests, this text is designed for a second or intermediate course in statistics for students in education and the behavioral sciences. the content coverage includes a number of regression and analysis of variance models, all subsumed under the general linear model (GLM). the text is designed for you to become a better-prepared researcher and a more intelligent consumer of research. It is assumed that you have already completed an introductory course in statistics (covering descriptive statistics up through t-tests). However, I do not assume that you have an extensive and/or recent training in mathematics. Many of you have only had algebra, some more than 20 years ago. Rest assured, you will do fine.

I believe that a text should serve as an effective instructional tool. You should find this text to be more than a reference book; you might actually use it to learn statistics (what an oxymoron, that a statistics book can actually teach something). This text is not a theoretical statistics book, nor is it a cookbook on computing statistics. Recipes have to be memorized, consequently you tend not to understand how or why you obtain the desired product. Besides, what happens if you run out of salt or forget to add butter?

Goals and content coverage

My goals for this text are lofty, but the effort and its effects will be worthwhile. First, the text provides a comprehensive coverage of topics that could be included in an undergraduate or graduate intermediate course in statistics. the text is flexible enough so that instructors can select those topics that they desire to cover as they deem relevant in their particular discipline. in other words, chapters and sections of chapters from this text can be included in a statistics course as the instructor sees fit. Most of the popular as well as many of the lesser-known procedures and models are described in the text. A

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