Understanding Statistics in Psychology, 9th edition

Published by Pearson (14 November 2024) © 2025

  • Dennis Howitt University of Loughborough
  • Duncan Cramer University of Loughborough
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Products list
$69.36 AUD
Instant access

Access details

  • Instant access once purchased
  • Offline access via app

Title overview

Be confident in putting core statistical techniques into practice

Understanding Statistics in Psychology provides an accessible introduction to the intimidating subject of statistics in psychology for students of all years and abilities.

This edition has clear explanations, diagrams and updated examples of real-life studies to bring the topic to life and show you how to put statistics into practice.

The new software-agnostic approach of this edition means that you will gain a solid understanding of statistics which can be applied to whichever statistical package you are using in your studies and in future research.

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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