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.

The Logic of Inferential Statistics : The Distinction Between Difference and Association Questions

The Logic of Inferential Statistics : The Distinction Between Difference and Association Questions

By a small sample, we may judge of the whole piece.

—Miquel de Cervantes from Don Quixote

Where We Have Been

To this point in the book, we have dealt with descriptive statistics, the procedures used to summarize data. More specifically, we have reviewed frequency distributions, as well as the measures that are employed for central tendency and variability. As you will recall, the frequency distribution provides a rapid view of the entire set of data, while the measures of central tendency and variability are single numbers that best summarize the location and spread of data, respectively. As Table 6.1 indicates, the specific procedure chosen depends on whether you are dealing with nominal, ordinal, ...

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