Introduction to SPSS Statistics in Psychology
For version 19 and earlier
5th Edition
Published on 31. March 2011
Book
Paperback/Softback
568 pages
978-0-273-73426-0 (ISBN)
Description
Introduction to SPSS Statistics in Psychology, 5th edition offers comprehensive and engaging coverage of how to carry out statistical analyses using SPSS Statistics.
Fully updated to include an even wider range of statistical methods and to incorporate the latest version of SPSS Statistics, this text offers clear, step by step instruction and advice to students on using SPSS Statistics to analyse psychological data.
For each statistical test, the text discusses
What the test is used for
When you should and shouldn't use it
Data requirements and any problems in usage
Step by step direction on how to carry out the test, using colour screenshots and labelled guidance on each part of the process
How to interpret and report the output
'At a glance' summary of steps taken to do each test
Suitable for students to use alongside lectures or independently when needing to grips with SPSS Statistics.
This book is supported by a companion website featuring a range of resources to help students in their studies. Self-test questions, additional datasets plus handy quick guides to carrying out tests can all be found at www.pearsoned.co.uk/howitt
"SPSS is the most widely used statistical analysis software suite in the social and behavioural sciences. It is used extensively in undergraduate psychology courses throughout the UK and USA. However psychology students find it notoriously difficult and often impossible to learn and use. Howitt and Cramers' SPSS Statistics in Psychology is an indispensible guide to the software, specially tailored for psychology students at all levels. The new edition is greatly enhanced by a several new features, including chapters on the analysis of moderator variables, statistical power, meta - analysis, and the use of SPSS syntax. It is superbly presented and illustrated with excellent step by step procedures and guides to the interpretation of results which even introductory level students will be able to follow. The supporting datasets and worked examples also provide an excellent resource for students and teachers. It has easily maintained its lead in a competitive field, and together with its companion textbooks, Introduction to Statistics (Fifth Edition) and Introduction to Research Methods (Third Edition), it has everything that apprentice and experienced researchers in psychology need." Professor Ronnie Wilson, University of Ulster
Fully updated to include an even wider range of statistical methods and to incorporate the latest version of SPSS Statistics, this text offers clear, step by step instruction and advice to students on using SPSS Statistics to analyse psychological data.
For each statistical test, the text discusses
What the test is used for
When you should and shouldn't use it
Data requirements and any problems in usage
Step by step direction on how to carry out the test, using colour screenshots and labelled guidance on each part of the process
How to interpret and report the output
'At a glance' summary of steps taken to do each test
Suitable for students to use alongside lectures or independently when needing to grips with SPSS Statistics.
This book is supported by a companion website featuring a range of resources to help students in their studies. Self-test questions, additional datasets plus handy quick guides to carrying out tests can all be found at www.pearsoned.co.uk/howitt
"SPSS is the most widely used statistical analysis software suite in the social and behavioural sciences. It is used extensively in undergraduate psychology courses throughout the UK and USA. However psychology students find it notoriously difficult and often impossible to learn and use. Howitt and Cramers' SPSS Statistics in Psychology is an indispensible guide to the software, specially tailored for psychology students at all levels. The new edition is greatly enhanced by a several new features, including chapters on the analysis of moderator variables, statistical power, meta - analysis, and the use of SPSS syntax. It is superbly presented and illustrated with excellent step by step procedures and guides to the interpretation of results which even introductory level students will be able to follow. The supporting datasets and worked examples also provide an excellent resource for students and teachers. It has easily maintained its lead in a competitive field, and together with its companion textbooks, Introduction to Statistics (Fifth Edition) and Introduction to Research Methods (Third Edition), it has everything that apprentice and experienced researchers in psychology need." Professor Ronnie Wilson, University of Ulster
More details
Edition
5th edition
Language
English
Place of publication
Harlow
United Kingdom
Publishing group
Pearson Education Limited
Target group
College/higher education
Dimensions
Height: 264 mm
Width: 196 mm
Thickness: 22 mm
Weight
1060 gr
ISBN-13
978-0-273-73426-0 (9780273734260)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Dennis Howitt | Duncan Cramer
Introduction to SPSS in Psychology
Book
05/2014
6th Edition
Pearson Education Limited
€37.13
Article exhausted; check for reprint
Content
Key differences between SPSS Statistics 19 and earlier versions
Part 1 Introduction to SPSS Statistics
1 A brief introduction to statistics 2 Basics of SPSS Statistics data entry and statistical analysis
Part 2 Descriptive statistics
3 Describing variables: Tables
4 Describing variables:Diagrams
5 Describing variables numerically: Averages, variation and spread
6 Shapes of distributions of scores
7 Standard deviation: The standard unit of measurement in statistics
8 Relationships between two or more variables: Tables
9 Relationships between two or more variables: Diagrams
10 Correlation coefficients: Pearson's correlation and Spearman's rho
11 Regression: Prediction with precision
Part 3 Significance testing and basic inferential tests
12 Standard error 13 The t-test: Comparing two samples of correlated/related/paired scores
14 The t-test: Comparing two groups of unrelated/uncorrelated scores
15 Confidence intervals
16 Chi-square: Differences between unrelated samples of frequency data 17 McNemar test: Differences between related samples of frequency data 18 Ranking tests for two groups: Non-parametric statistics 19 Rts for three or more groups: Non-parametric statistics
Part 4 Analysis of variance
20 The variance ratio test: Using the F-ratio to compare two variances 21 Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA
22 Analysis of variance for correlated scores or repeated measures 23 Two-way analysis of variance for unrelated/uncorrelated scores 24 Multiple comparisons in ANOVA
25 Two-way mixed analysis of variance (ANOVA) 26 Analysis of covariance (ANCOVA)
27 Multivariate analysis of variance (MANOVA)
28 Discriminant function analysis (for MANOVA)
Part 5 More advanced correlational statistics
29 Partial correlation 30 Factor analysis
31 Item reliability and inter-rater agreement 32 Stepwise multiple regression
33 Simultaneous or standard multiple regression
34 Simple mediational analysis 35 Hierarchical multiple regression 36 Moderator analysis with continuous predictor variables
Part 6 Advanced qualitative or nominal techniques
37 Log-linear analysis
38 Multinomial logistic regression 39 Binomial logistic regression
Part 7 Data handling procedures
40 Reading ASCII or text files into the Data Editor 41 Missing values 42 Recoding values 43 Computing a scale score with no missing values 44 Computing a scale score with some values missing 45 Computing a new group variable from existing group variables
46 Selecting cases 47 Samples and populations: Generating a random sample 48 Inputting a correlation matrix 49 Checking the accuracy of data inputing
Part 8 Linear structural relationship (LISREL) analysis
50 Basics of LISREL and LISREL data entry
51 Confirmatory factor analysis with LISREL
52 Simple path analysis with measurement error uncorrected 53 Simple path analysis with latent variables 54 Simple path analysis controlling for alpha reliability
Part 9 Other statistical procedures
55 Statistical power analysis: Sample size estimation
56 Meta-analysis
Appendix: Some other statistics in SPSS Statistics
Part 1 Introduction to SPSS Statistics
1 A brief introduction to statistics 2 Basics of SPSS Statistics data entry and statistical analysis
Part 2 Descriptive statistics
3 Describing variables: Tables
4 Describing variables:Diagrams
5 Describing variables numerically: Averages, variation and spread
6 Shapes of distributions of scores
7 Standard deviation: The standard unit of measurement in statistics
8 Relationships between two or more variables: Tables
9 Relationships between two or more variables: Diagrams
10 Correlation coefficients: Pearson's correlation and Spearman's rho
11 Regression: Prediction with precision
Part 3 Significance testing and basic inferential tests
12 Standard error 13 The t-test: Comparing two samples of correlated/related/paired scores
14 The t-test: Comparing two groups of unrelated/uncorrelated scores
15 Confidence intervals
16 Chi-square: Differences between unrelated samples of frequency data 17 McNemar test: Differences between related samples of frequency data 18 Ranking tests for two groups: Non-parametric statistics 19 Rts for three or more groups: Non-parametric statistics
Part 4 Analysis of variance
20 The variance ratio test: Using the F-ratio to compare two variances 21 Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA
22 Analysis of variance for correlated scores or repeated measures 23 Two-way analysis of variance for unrelated/uncorrelated scores 24 Multiple comparisons in ANOVA
25 Two-way mixed analysis of variance (ANOVA) 26 Analysis of covariance (ANCOVA)
27 Multivariate analysis of variance (MANOVA)
28 Discriminant function analysis (for MANOVA)
Part 5 More advanced correlational statistics
29 Partial correlation 30 Factor analysis
31 Item reliability and inter-rater agreement 32 Stepwise multiple regression
33 Simultaneous or standard multiple regression
34 Simple mediational analysis 35 Hierarchical multiple regression 36 Moderator analysis with continuous predictor variables
Part 6 Advanced qualitative or nominal techniques
37 Log-linear analysis
38 Multinomial logistic regression 39 Binomial logistic regression
Part 7 Data handling procedures
40 Reading ASCII or text files into the Data Editor 41 Missing values 42 Recoding values 43 Computing a scale score with no missing values 44 Computing a scale score with some values missing 45 Computing a new group variable from existing group variables
46 Selecting cases 47 Samples and populations: Generating a random sample 48 Inputting a correlation matrix 49 Checking the accuracy of data inputing
Part 8 Linear structural relationship (LISREL) analysis
50 Basics of LISREL and LISREL data entry
51 Confirmatory factor analysis with LISREL
52 Simple path analysis with measurement error uncorrected 53 Simple path analysis with latent variables 54 Simple path analysis controlling for alpha reliability
Part 9 Other statistical procedures
55 Statistical power analysis: Sample size estimation
56 Meta-analysis
Appendix: Some other statistics in SPSS Statistics