Introduction to Spss in Psychology

by Howitt, Dennis; Cramer, Duncan

• ISBN13: 9780131399860
• ISBN10: 0131399861
• Edition: 3rd
• Format: Paperback
• Copyright: 2005-12-31
• Publisher: Prentice Hall

Summary

Introduction to SPSS in Psychology Using SPSS effectively is about student confidence. With Introduction to SPSS in Psychology, students will quickly master statistical analysis with SPSS. Screenshots of all of the steps for each statistical technique give students that crucial confidence that they are on top of their analysis. Key features of the output are highlighted graphically and explained. Models of how to report the findings are provided for all techniques. Introduction to SPSS in Psychology is designed for use with SPSS12 and 13 but is just as effective with SPSS 10 and 11. It presents to students, beginners as well as more advanced students, an excellent, uncluttered, hands-on guide to the most common statistical package for psychologists. Introduction to SPSS in Psychology can be used alone or to complement the AUTHORs' Introduction to Research Methods in Psychology and Introduction to Statistics in Psychology also published by Prentice Hall. Key Features - A full range of statistics are covered, from the simplest to the advanced, all with equal clarity - Explains the practical application of statistics to data - Explains step-by-step how to enter, analyse, interpret and report data - Gives detail about what to report and how to report it - Web based supplementary material available Dennis Howitt and Duncan Cramer are both Readers in Psychology at Loughborough University

Table of Contents

Basis of SPSS data entry and statistical analysis	p. 1
Describing variables : tables and diagrams	p. 16
Describing variables numerically : averages, variation and spread	p. 30
Shapes of distributions of scores	p. 35
Standard deviation : the standard unit of measurement in statistics	p. 40
Relationships between two or more variables : diagrams and tables	p. 45
Correlation coefficients : Pearson's correlation and Spearman's rho	p. 56
Regression : prediction with precision	p. 64
Samples and populations : generating a random sample	p. 72
Selecting cases	p. 76
Standard error	p. 80
The t-test : comparing two samples of correlated/related scores	p. 83
The t-test : comparing two groups of unrelated/uncorrelated scores	p. 88
Chi-square : differences between samples of frequency data	p. 93
Missing values	p. 106
Recoding values	p. 112
Computing new variables	p. 117
Ranking tests : non-parametric statistics	p. 120
The variance ratio test : using the F-ratio to compare two variances	p. 127
Analysis of variance (ANOVA) : introducing to the one-way unrelated or uncorrelated ANOVA	p. 131
Analysis of variance for correlated scores or repeated measures	p. 135
Two-way analysis of variance for unrelated/uncorrelated scores	p. 140
Multiple comparisons in ANOVA	p. 147
Analysis of covariance (ANCOVA) and two-way mixed analysis of variance (ANOVA) designs	p. 152
Reading ASCII or text files into the data editor	p. 163
Partial correlation	p. 168
Factor analysis	p. 171
Stepwise multiple regression	p. 178
Hierarchical multiple regression	p. 185
Item reliability and inter-rater agreement	p. 192
Log-linear analysis	p. 200
Multinomial logistic regression	p. 208
Binomial logistic regression	p. 219
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