Using a truly accessible and reader-friendly approach, this comprehensive introduction to statistics redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.

Finding Differences With Nominal Data—I : The Goodness-of-Fit Chi-Square

Finding Differences With Nominal Data—I : The Goodness-of-Fit Chi-Square

Statistics may be defined as “a body of methods for making wise decisions in the face of uncertainty.”

—W. A. Wallis

we begin our exploration of inferential statistical procedures with an examination of relationships using the simplest type of data. Recall that nominal data consist only of frequencies. An example of nominal data would be if you were to determine how many members of a group consider themselves to be Republicans, how many consider themselves to be Democrats, how many have some other party affiliation, and how many have no affiliation at all. You would simply determine the frequency in each category.

In this chapter and in Chapter 8, we will be utilizing procedures that do not make ...

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