For one-quarter/semester courses that focus on the basics or combine statistics with research methods.
By using definitional formulas to emphasize the concepts of statistics, rather than rote memorization, students work problems in a way that keeps them constantly aware of the underlying logic of what they are doing.
Here, in the fourth edition of Statistics for the Behavioral and Social Sciences, the authors have refined their text by building off an already well-established approach - emphasizing the intuitive, deemphasizing the mathematical, and explaining everything in direct, simple language - but also going beyond these principles to both further student understanding and stimulate the long-suffering community of statistics instructors. By using definitional formulas to emphasize the concepts of statistics, rather than rote memorization, students work problems in a way that keeps them constantly aware of the underlying logic of what they are doing.
"synopsis" may belong to another edition of this title.
Because today statistics are done by computer, not by hand, and the majority of social science majors are human- and word-oriented, not math and number oriented, this text offers a different approach to teaching statistics. Focusing on understanding, it emphasizes the intuitive, de-emphasizes the mathematical, explains everything in clear, simple language, and requires students to put what they know into words rather than to recite formulas.
Because today's statistics are done by computer, not by hand, and the majority of individuals in the social sciences are human- and word-oriented, not math and number oriented, this book offers a different approach to teaching statistics. Focusing on understanding, it emphasizes the intuitive, de-emphasizes the mathematical, and explains everything in clear, simple language. The book uses definitional formulas and encourages readers put words to what they know by writing essays rather than reciting formulas. The volume offers a comprehensive overview of key statistical concepts including the mean, variance, standard deviation, and z scores, correlation and prediction, key ingredients for inferential statistics: the normal curve, probability, and population versus sample and introduction to hypothesis testing, decision error, statistical power, and effect size, an introduction to the t test, analysis of variance, chi-square and strategies when population distributions are not normal and making sense of advanced statistical procedures in research articles.
"About this title" may belong to another edition of this title.
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