A book that focuses on the logic behind the concepts of statistics for psychology, using definitional formulas rather than emphasizing rote memorization. Clearly written, each procedure is conveyed both numerically and verbally, with many visual examples to illustrate the text. It takes the reader from basic procedures through analysis of variance (ANOVA), and not only teaches statistics, but also prepares the user to read and understand research articles as well. This book is an introduction to statistics for psychology, covering such topics as order in a group of numbers; mean, variance, standard deviation, and Z scores; correlation; prediction; the normal curve, probability, and population versus sample; hypothesis testing; the t test; analysis of variance; chi-square tests; the general linear model; and making sense of advanced statistical procedures in research articles. For statisticians, psychologists and those involved in psychological research in the behavioral and social sciences.
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Class-tested and developed over two decades, the material for this innovative text reflects recent changes in both research practice and in the teaching of statistics for psychology: 1) Statistics are done by computer, not by hand, so the text stresses deep understanding, not brief explanation followed by the usual plugging numbers into formulas. 2) The majority of psychology majors are human-and word-oriented, not math-oriented, so this text employs their way of learning--for example, requiring them to put what they learn into words lay persons can understand.
Designed to prepare readers to "do" statistics, to read statistical research, and to understand articles, this book emphasizes the intuitive, deemphasizes the mathematical, and explains everything in clear, simple language. It bases all explanations, examples, and practice problems on definitional formulas, and teaches each procedure verbally, numerically, and often visually -- describing the same examples in each of these ways. It gives examples of how each method is reported in the journals, and uses examples drawn from clinical, organizational, and educational psychology as well as from experimental, social, developmental, and other fields. Covers: Displaying the Order in a Group of Numbers; The Mean, Variance, Standard Deviation, and Z Scores; Correlation; Prediction; Some Key Ingredients for Inferential Statistics; Introduction to Hypothesis Testing; Hypothesis Tests with Means of Samples; Statistical Power and Effect Size; The t Test for Dependent Means; The t Test for Independent Means; Introduction to the Analysis of Variance; and The Structural Model in the Analysis of Variance. Present the general linear model that integrates all the major techniques covered. Acknowledges the on-going -- and very hotly debated -- controversy in statistics over the value of significance tests and the associated proposals for replacing them with effect size, point estimates, and confidence intervals. For anyone needing an introduction to, or refresher of, contemporary statistics with applications to psychology.
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