Statistics for Psychology

Statistics for Psychology

Paperback

By (author) Arthur Aron, By (author) Elaine N. Aron, By (author) Elliot Coups, By (author) Cole Publishing

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Format
Hardback $192.34
  • Publisher: Pearson
  • Format: Paperback | 744 pages
  • Dimensions: 203mm x 254mm x 24mm | 1,160g
  • Publication date: 1 November 2008
  • ISBN 10: 0132365022
  • ISBN 13: 9780132365024
  • Edition: 5
  • Edition statement: 5th International edition
  • Sales rank: 163,108

Product description

This author team is committed to making statistics a highlight for psychology students! Now, in a 5th edition, Statistics for Psychology, continues to be an accessible, current, and interesting approach to statistics. With each revision, the authors have maintain those things about the book that have been especially appreciated, while reworking the text to take into account the feedback, their our own experiences, and advances and changes in the field. The fifth edition of this popular text uses definitional formulas to emphasize concepts of statistics, rather than rote memorization. This approach constantly reminds students of the logic behind what they are learning, and each procedure is taught both verbally and numerically, which helps to emphasize the concepts. Thoroughly revised, with new content and many new practice examples, this text takes the reader from basic procedures through analysis of variance (ANOVA). While learning statistics, students also learn how to read and interpret current research.

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Table of contents

1. Displaying the order in a group of numbers. 2. Central tendency and variability. 3. Some key ingredients for inferential statistics: Z scores, the normal curve, sample versus population, and probability. 4. Introduction to hypothesis testing. 5. Hypothesis testing with means of samples. 6. Making sense of statistical significance: Effect size and statistical power. 7. Introduction to the t test: Single sample and dependent means. 8. The t test for independent means. 9. Introduction to the analysis of variance. 10. Factorial analysis of variance. 11. Correlation. 12. Prediction. 13. Chi-square tests. 14. Strategies when population distributions are not normal: Data transformations and rank-order tests. 15. Integration and the general linear model. 16. Making sense of advanced statistical procedures in research articles.