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Understanding Statistics in Psychology with SPSS IE

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ISBN13
9781292134215
יצא לאור ב
Harlow
מהדורה
7th New edition
עמודים / Pages
IE
פורמט
Paperback / softback
תאריך יציאה לאור
10 בפבר׳ 2017
מחליף את פריט
9781292000749
Revised edition of the authors' Introduction to statistics in psychology, 2013.
Understanding Statistics in Psychology with SPSS 7th edition, offers students a trusted, straightforward, and engaging way of learning how to carry out statistical analyses and use SPSS with confidence. Comprehensive and practical, the text is organised by short, accessible chapters, making it the ideal text for undergraduate psychology students needing to get to grips with Statistics in class or independently. Clear diagrams and full colour screenshots from SPSS make the text suitable for beginners while the broad coverage of topics ensures that students can continue to use it as they progress to more advanced techniques. Key features * Now combines coverage of statistics with full guidance on how to use SPSS to analyse data * Suitable for use with all versions of SPSS * Examples from a wide range of real psychological studies illustrate how statistical techniques are used in practice * Includes clear and detailed guidance on choosing tests, interpreting findings and reporting and writing up research * Student focused pedagogical approach including o Key concept boxes detailing important terms o Focus on sections exploring complex topics in greater depth o 'Explaining statistics sections clarify important statistical concepts'.
מידע נוסף
מהדורה 7th New edition
עמודים / Pages IE
מחליף את פריט 9781292000749
פורמט Paperback / softback
ISBN10 1292134216
יצא לאור ב Harlow
תאריך יציאה לאור 10 בפבר׳ 2017
תוכן עניינים Contents vii Guided tour xx Introduction xxv Acknowledgements xxvii 1 Why statistics? Part 1 Descriptive statistics 2 Some basics: Variability and measurement 3 Describing variables: Tables and diagrams 4 Describing variables numerically: Averages, variation and spread 5 Shapes of distributions of scores 6 Standard deviation and z-scores: Standard unit of measurement in statistics 7 Relationships between two or more variables: Diagrams and tables 8 Correlation coefficients: Pearson's correlation and Spearman's rho 9 Regression: Prediction with precision Part 2 Significance testing 10 Samples from populations 11 Statistical significance for the correlation coefficient: Practical introduction to statistical inference 12 Standard error: Standard deviation of the means of samples 13 Related t-test: Comparing two samples of related/correlated/paired scores 14 Unrelated t-test: Comparing two samples of unrelated/ uncorrelated/independent scores 15 What you need to write about your statistical analysis 16 Confidence intervals 17 Effect size in statistical analysis: Do my findings matter? 18 Chi-square: Differences between samples of frequency data 19 Probability 20 One-tailed versus two-tailed significance testing 21 Ranking tests: Nonparametric statistics Part 3 Introduction to analysis of variance 22 Variance ratio test: F-ratio to compare two variances 23 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA 24 ANOVA for correlated scores or repeated measures 25 Two-way or factorial ANOVA for unrelated/uncorrelated scores: Two studies for the price of one? 26 Multiple comparisons in ANOVA: A priori and post hoc tests 27 Mixed-design ANOVA: Related and unrelated variables together 28 Analysis of covariance (ANCOVA): Controlling for additional variables 29 Multivariate analysis of variance (MANOVA) 30 Discriminant (function) analysis - especially in MANOVA 31 Statistics and analysis of experiments Part 4 More advanced correlational statistics 32 Partial correlation: Spurious correlation, third or confounding variables, suppressor variables 33 Factor analysis: Simplifying complex data 34 Multiple regression and multiple correlation 35 Path analysis 36 Analysis of a questionnaire/survey project Part 5 Assorted advanced techniques 37 Meta-analysis: Combining and exploring statistical findings from previous research 38 Reliability in scales and measurement: Consistency and agreement 39 Influence of moderator variables on relationships between two variables 40 Statistical power analysis: Getting the sample size right Part 6 Advanced qualitative or nominal techniques 41 Log-linear methods: Analysis of complex contingency tables 42 Multinomial logistic regression: Distinguishing between several different categories or groups 43 Binomial logistic regression Appendices Glossary References Index