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    Introduction to SPSS in Psychology (Paperback) By (author) Dennis Howitt, By (author) Duncan Cramer

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    DescriptionIntroduction to SPSS Statistics in Psychology gives you a straight-forward way of learning to carry out statistical analyses and use SPSS with confidence. This edition is fully updated to include the latest version of SPSS Statistics, and covers the same wide range of statistical tests that made the previous edition such an trusted guide. Clear diagrams and screenshots from SPSS version 22 make the text suitable for beginners while the broad coverage of topics ensures that you can continue to use it as you progress to more advanced techniques.


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    Title
    Introduction to SPSS in Psychology
    Authors and contributors
    By (author) Dennis Howitt, By (author) Duncan Cramer
    Physical properties
    Format: Paperback
    Number of pages: 592
    Width: 196 mm
    Height: 261 mm
    Thickness: 22 mm
    Weight: 1,074 g
    Language
    English
    ISBN
    ISBN 13: 9781292000695
    ISBN 10: 1292000694
    Classifications

    BIC E4L: PSY
    B&T Book Type: NF
    Nielsen BookScan Product Class 3: S2.2T
    B&T Merchandise Category: TXT
    LC classification: BF
    B&T General Subject: 670
    BIC subject category V2: JMBT
    Abridged Dewey: 150
    BISAC V2.8: PSY032000, PSY000000
    DC23: 150.287
    Thema V1.0: JMBT
    Edition
    6, Revised
    Edition statement
    6th Revised edition
    Publisher
    Pearson Education Limited
    Imprint name
    Pearson Education Limited
    Publication date
    03 September 2014
    Publication City/Country
    Harlow
    Table of contents
    Introduction xvi Key differences between SPSS Statistics 22 and earlier versions xix Part 1 Introduction to SPSS Statistics 1 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 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 Ranking tests 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 one-way correlated scores or repeated measures 23 Two-way analysis of variance for unrelated/uncorrelated scores 24 Multiple comparisons in ANOVA 25 Two-way analysis of variance for correlatedscores or repeated measures 26 Two-way mixed analysis of variance (ANOVA) 27 Analysis of covariance (ANCOVA) 28 Multivariate analysis of variance (MANOVA) 29 Discriminant (function) analysis (for MANOVA) Part 5 More advanced correlational statistics 30 Partial correlation 31 Factor analysis 32 Item reliability and inter-rater agreement 33 Stepwise multiple regression 34 Simultaneous or standard multiple regression 35 Simple mediational analysis 36 Hierarchical multiple regression 37 Moderator analysis with continuous predictor variables Part 6 Advanced qualitative or nominal techniques 38 Log-linear analysis 39 Multinomial logistic regression 40 Binomial logistic regression Part 7 Data handling procedures 41 Reading ASCII or text files into the Data Editor 42 Missing values 43 Recoding values 44 Computing a scale score with no missing values 45 Computing a scale scorewith some values missing 46 Computing new groups 47 Selecting cases 48 Samples and populations: Generating a random sample 49 Inputting a correlation matrix 50 Checking accuracy of data input Part 8 Other statistical procedures 51 Statistical power analysis: Sample size estimation 52 Meta-analysis Appendix: Some other statistics in SPSS Statistics Glossary Index