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Basic psychological measurement, research designs, and statistics without math Book

Basic psychological measurement, research designs, and statistics without math
Basic psychological measurement, research designs, and statistics without math, , Basic psychological measurement, research designs, and statistics without math has a rating of 2.5 stars
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Basic psychological measurement, research designs, and statistics without math, , Basic psychological measurement, research designs, and statistics without math
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  • Basic psychological measurement, research designs, and statistics without math
  • Written by author Marty Sapp
  • Published by Springfield, Ill. : Charles C. Thomas Publishers, c2006., February 2006
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This book is designed to give students the confidence to understand theoretically issues like reliability and validity and through calculator and statistical packages such as Microsoft Excel, SPSS, SAS, and EQS. Students are shown that they can easily find reliability and validity measures without mathematics. Once exposed to measurement concepts, research design is the next topic. With this area, the topic of variables are cover-dependent, dependent, moderator, control, suppressor, and intervening. Additionally, the concepts of interval and external validity are discussed, and research designs are covered such as one-group, two-group, multiple treatment, factorial, quasi-experimental, and nested designs. Measures of central tendency and variability are presented, and examples are connected to a calculator and the statistical packages. The general univariate statistics are examined such as t-tests, analysis of variance, simple regression, analysis of covariance, nest analysis of variance, and the univariate and multivariate approaches to repeated measures. Two-way analysis of variance with repeated measures on one factor are covered along with multivariate matched pairs analysis, totally within repeated measures designs, and doubly multivariate repeated measures. Multiple regression, structured coefficients within multiple regression, interaction effects within multiple regression, cross-validation within multiple regression, logistic regression, multivariate regression, multilevel re-gression, factorial analysis of variance and covariance, stepdown analysis, discriminant analysis, exploratory and factor analysis, structural equations modeling, canonical correlation, and loglinear analysis are discussed. Finally, a nonmathematical treatment of psychological measurement, research designs, and statistics is presented.


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