SPSS for Intermediate Statistics Use and Interpretation, Second Edition / Edition 2

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Overview

Intended as a supplement for intermediate statistics courses taught in depts of psych, ed, business, and other health, behavioral, and social sciences.

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Product Details

  • ISBN-13: 9780805847901
  • Publisher: Taylor & Francis
  • Publication date: 8/16/2004
  • Edition description: Older Edition
  • Edition number: 2
  • Pages: 256
  • Product dimensions: 8.40 (w) x 10.80 (h) x 0.70 (d)

Meet the Author

Nancy Leech is an Associate Professor at the University of Colorado Denver. She received her Ph.D. in education with an emphasis on research and statistics from Colorado State University in 2002. Dr. Leech is currently teaching graduate level courses in research, statistics, and measurement. Her area of research is promoting new developments and better understandings in applied qualitative, quantitative, and mixed methodologies.

Karen C. Barrett is Professor of Human Development and Family Studies with a joint appointment in Psychology at Colorado State University. She received her Ph.D. from the University of Denver. She is Assistant Department head of HDFS and teaches graduate level research methods and statistics courses. Her research regards emotion regulation and its influence on development; social emotions such as guilt and shame; and family and cultural influences on emotions.

George A. Morgan is Emeritus Professor of Education and Human Development at Colorado State University. He received his Ph.D. in child development and psychology from Cornell University. In addition to writing textbooks on SPSS and research methods, he has advised many PhD students in education and related fields. Over the past 35 years, he has conducted a program of research on children’s motivation to master challenging tasks.

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Table of Contents

Introduction and Review of Basic Statistics With SPSS. Data Coding and Exploratory Analysis (EDA). Several Measures of Reliability. Exploratory Factor Analysis and Principal Components Analysis. Selecting and Interpreting Inferential Statistics. Multiple Regression. Logistic Regression and Discriminant Analysis. Factorial ANOVA and ANCOVA. Repeated Measures and Mixed ANOVAs. Multivariate Analysis of Variance (MANOVA) and Canonical Correlation. Multilevel Linear Modeling/Hierarchical Linear Modeling. Appendices.

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