Introduction to Spss in Psychology

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Edition: 3rd
Format: Paperback
Pub. Date: 2005-12-31
Publisher(s): Prentice Hall
List Price: $65.63

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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 analysisp. 1
Describing variables : tables and diagramsp. 16
Describing variables numerically : averages, variation and spreadp. 30
Shapes of distributions of scoresp. 35
Standard deviation : the standard unit of measurement in statisticsp. 40
Relationships between two or more variables : diagrams and tablesp. 45
Correlation coefficients : Pearson's correlation and Spearman's rhop. 56
Regression : prediction with precisionp. 64
Samples and populations : generating a random samplep. 72
Selecting casesp. 76
Standard errorp. 80
The t-test : comparing two samples of correlated/related scoresp. 83
The t-test : comparing two groups of unrelated/uncorrelated scoresp. 88
Chi-square : differences between samples of frequency datap. 93
Missing valuesp. 106
Recoding valuesp. 112
Computing new variablesp. 117
Ranking tests : non-parametric statisticsp. 120
The variance ratio test : using the F-ratio to compare two variancesp. 127
Analysis of variance (ANOVA) : introducing to the one-way unrelated or uncorrelated ANOVAp. 131
Analysis of variance for correlated scores or repeated measuresp. 135
Two-way analysis of variance for unrelated/uncorrelated scoresp. 140
Multiple comparisons in ANOVAp. 147
Analysis of covariance (ANCOVA) and two-way mixed analysis of variance (ANOVA) designsp. 152
Reading ASCII or text files into the data editorp. 163
Partial correlationp. 168
Factor analysisp. 171
Stepwise multiple regressionp. 178
Hierarchical multiple regressionp. 185
Item reliability and inter-rater agreementp. 192
Log-linear analysisp. 200
Multinomial logistic regressionp. 208
Binomial logistic regressionp. 219
Table of Contents provided by Blackwell. All Rights Reserved.

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