Basic Psychological Measurement, Research Designs, And Statistics Without Math,Used
Basic Psychological Measurement, Research Designs, And Statistics Without Math,Used

Basic Psychological Measurement, Research Designs, And Statistics Without Math,Used

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SKU: SONG0398076154
UPC: 9780398076153
Brand: Charles C Thomas Pub Ltd
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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 coverdependent, dependent, moderator, control, suppressor, and intervening. Additionally, the concepts of interval and external validity are discussed, and research designs are covered such as onegroup, twogroup, multiple treatment, factorial, quasiexperimental, 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 ttests, analysis of variance, simple regression, analysis of covariance, nest analysis of variance, and the univariate and multivariate approaches to repeated measures. Twoway 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, crossvalidation within multiple regression, logistic regression, multivariate regression, multilevel regression, 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.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

  • Q: What is the main focus of 'Basic Psychological Measurement, Research Designs, And Statistics Without Math'? A: The book primarily focuses on providing students with a comprehensive understanding of psychological measurement, research designs, and the statistical methods used in these fields without the need for advanced mathematics.
  • Q: Who is the author of this book? A: The author of the book is Marty Sapp.
  • Q: What topics are covered in the book related to research designs? A: The book covers various research designs, including one-group, two-group, multiple treatment, factorial, quasi-experimental, and nested designs.
  • Q: Is this book suitable for beginners in psychology? A: Yes, the book is designed for beginners and aims to build confidence in understanding key concepts like reliability and validity without requiring advanced math skills.
  • Q: How many pages does this book contain? A: The book contains a total of 272 pages.
  • Q: What type of binding does the book have? A: The book is available in paperback binding.
  • Q: When was 'Basic Psychological Measurement, Research Designs, And Statistics Without Math' published? A: The book was published on February 7, 2006.
  • Q: Does the book include practical applications of statistics? A: Yes, the book provides practical applications of statistics using calculator examples and statistical software like Microsoft Excel, SPSS, and SAS.
  • Q: What is the condition of the book? A: The book is brand new, ensuring that readers receive it in excellent condition.
  • Q: Can this book help with understanding multivariate statistics? A: Yes, the book discusses various multivariate statistical methods, including multiple regression, exploratory factor analysis, and structural equations modeling.

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