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Author:   Dennis Howitt ,  Duncan Cramer
Publisher:   Pearson Education Limited
Imprint:   Pearson Education Limited
Edition:   9th edition
ISBN:  

9781292465180

ISBN 10:   1292465182
Publication Date:   12 November 2024
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Preface Why statistics? Part 1 Descriptive statistics Some basics: Variability and measurement Describing variables: Tables and diagrams Describing variables numerically: Averages, variation and spread Shapes of distributions of scores Standard deviation and z-scores: Standard unit of measurement in statistics Relationships between two or more variables: Diagrams and tables Correlation coefficients: Pearson’s correlation and Spearman's rho Regression: Prediction with precision Part 2 Significance testing Samples from populations Statistical significance for the correlation coefficient: Practical introduction to statistical inference Standard error: Standard deviation of the means of samples Related or paired-samples t-test: Comparing two samples of related/correlated/paired scores Unrelated or independent-samples t-test: Comparing two samples of unrelated/uncorrelated/independent scores What you need to write about your statistical analysis Confidence intervals Effect size in statistical analysis: Do my findings matter? Chi-square: Differences between samples of frequency data Probability One- versus two-tailed or -sided significance testing Ranking tests: Nonparametric statistics Part 3 Introduction to analysis of variance Variance ratio test: F-ratio to compare two variances Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA ANOVA for correlated scores or repeated measures Two-way or factorial ANOVA for unrelated/uncorrelated scores: Two studies for the price of one? Multiple comparisons in ANOVA: A priori and post hoc tests Mixed-design ANOVA: Related and unrelated variables together Analysis of covariance (ANCOVA): Controlling for additional variables Multivariate analysis of variance (MANOVA) Discriminant (function) analysis – especially in MANOVA Statistics and analysis of experiments Part 4 More advanced correlational statistics Partial correlation: Spurious correlation, third or confounding variables, suppressor variables Factor analysis: Simplifying complex data Multiple regression and multiple correlation Path analysis Analysis of a questionnaire/survey project Part 5 Assorted advanced techniques Meta-analysis: Combining and exploring statistical findings from previous research Reliability in scales and measurement: Consistency and agreement Influence of moderator variables on relationships between two variables Statistical power analysis: Getting the sample size right Part 6 Advanced qualitative or nominal techniques Log-linear methods: Analysis of complex contingency tables Multinomial logistic regression: Distinguishing between several different categories or groups Binomial logistic regression Part 7 Bringing things together Data mining and Big Data Towards a masterplan Appendices Glossary References Index

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Author Information

Dennis Howitt is a reader in Psychology at Loughborough University, a chartered forensic psychologist and fellow of the British Psychological Society, with a specific interest in the study of mass communications and the application of psychology to social issues. Duncan Cramer is an emeritus professor at Loughborough University with a specific interest in topics such as mental health, personality, personal relationships, organizational commitment, psychotherapy and counselling.

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