Fundamental Statistics for the Behavioral Sciences
By David C. Howell
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FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test. This practical approach provides students with an understanding of the logic behind the statistics, so they understand why and how certain methods are used -- rather than simply carry out techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. Written in an informal style, the text includes an abundance of real data and research studies that provide a real-life perspective and help students learn and understand concepts. In alignment with current trends in statistics in the behavioral sciences, the text emphasizes effect sizes and meta-analysis, and integrates frequent demonstrations of computer analyses through SPSS and R.
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About this product
FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test. This practical approach provides students with an understanding of the logic behind the statistics, so they understand why and how certain methods are used -- rather than simply carry out techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. Written in an informal style, the text includes an abundance of real data and research studies that provide a real-life perspective and help students learn and understand concepts. In alignment with current trends in statistics in the behavioral sciences, the text emphasizes effect sizes and meta-analysis, and integrates frequent demonstrations of computer analyses through SPSS and R.
Each chapter begins with a listing of terms to be used in the chapter that were introduced earlier. The author includes terms that students have the hardest time understanding, and which consequently warrant repeating. Especially in the early chapters, terms are redefined not only when first introduced, but also when used a second, third, or even a fourth time.
The book's clear writing, clear definition of terms, and use of worked out examples help students understand some of the more difficult concepts in statistics.
The text is full of applications, with real data used in all examples. This places a real life perspective on the material and allows for deeper student understanding. The applications are listed on the inside front covers.
Based on the author's belief that formulas are most helpful in helping students learn concepts, rather than for computation, formulas used in the book are definitional rather than for purposes of calculation.
Table of contents
Chapters
Chapter 1. IntroductionPreview this chapter
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