Statistics for Psychology
United States Edition
4th Edition
Published on 4. October 2005
Book
Hardback
768 pages
978-0-13-193167-1 (ISBN)
Description
The fourth 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). Students cover statistics and also learn to read and inderstand research articles.
More details
Edition
4th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Width: 263 mm
Thickness: 34 mm
Weight
1560 gr
ISBN-13
978-0-13-193167-1 (9780131931671)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Book
04/2008
5th Edition
Pearson
€84.31
Article exhausted; check for reprint
Previous edition
Book
08/2002
3rd Edition
Pearson
€88.03
Article exhausted; check for reprint
Content
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.
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.