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1

Introduction to SPSS in Psychology.

HOWITT Dennis ; CRAMER Duncan

PEARSON EDUCATION

2017

431

164.71-HOWIT

PSYCHOMETRICS ; SOCIAL STATISTICS


Number of copies : 1
No. Call n° Bar code Commentary
1 [available]

Comment : For version 23 and earlier

ISBN 13 : 978-1292186665

Contents :
Introduction
Part 1 Introduction to SPSS
1 Brief introduction to statistics
2 Basics of SPSS 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 Relationships between two or more variables: Tables
8 Relationships between two or more variables: Diagrams
9 Correlation coefficients: Pearson's correlation and Spearman's rho
10 Regression: Prediction with precision

Part 3 Significance testing and basic inferential tests
11 Related t-test: Comparing two samples of related/correlated/paired scores
12 Unrelated t-test: Comparing two groups of unrelated/uncorrelated/independent scores
13 Confidence intervals
14 Chi-square: Differences between unrelated samples of frequency data
15 McNemar's test: Differences between related samples of frequency data
16 Ranking tests for two groups: Non-parametric statistics
17 Ranking tests for three or more groups: Non-parametric statistics

Part 4 Analysis of variance
18 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA
19 Analysis of variance for one-way correlated scores or repeated measures
20 Two-way analysis of variance for unrelated/uncorrelated scores
21 Multiple comparison in ANOVA
22 Analysis of variance for two-way correlated scores or repeated measures
23 Two-way mixed analysis of variance (ANOVA)
24 Analysis of covariance (ANCOVA)
25 Multivariate analysis of variance (MANOVA)

Part 5 More advanced statistics
26 Partial correlation
27 Factor analysis
28 Item reliability and inter-rater agreement
29 Stepwise multiple regression
30 Simultaneous or standard multiple regression
31 Simple mediational analysis
32 Hierarchical multiple regression
33 Log-linear analysis
34 Meta-analysis

Part 6 Data handling procedures
35 Missing values
36 Recoding values
37 Computing a scale score with some values missing
38 Computing a new group variable from existing group variables
39 Selecting cases
40 Reading ASCII or text files into the Data Editor

Glossary
Index

Language : English

Print : 7ème

Figure(s) : Tableau(x) ; Schémas

Location : Nice Library

Material : Paper

Statement : Présent

Owner : Bibliothèque