BPS Core Textbooks Series

Developed in collaboration with the British Psychological Society

Chapter 17 – The Wisdom of the Crowd: Reification and the Authority of Statistics

Chapter Summary

This chapter explores the historical and conceptual development of statistics in psychology, focusing on how numerical tools such as correlation, regression, the Analysis of Variance (ANOVA), and significance testing (p-values) became central to psychological inquiry. Beginning in the nineteenth century with figures such as Francis Galton and Karl Pearson, the chapter traces how early efforts to quantify human differences led to the formalisation of key statistical methods. It examines the innovations of influential statisticians, including William Gosset and Ronald Fisher, highlighting how their solutions to specific methodological challenges shaped modern psychology. Central to the chapter is the critical concept of reification: the tendency to treat abstract constructs (such as intelligence, anxiety, or personality) as if they were fixed, measurable entities. Drawing on Joel Michell’s critique of measurement in psychology, the chapter examines the epistemological, ontological, and political risks of treating statistical abstractions as psychological realities. It also explores how statistical reasoning granted psychology institutional power, but at the cost of potential conceptual distortion. The chapter invites us to interrogate not only how psychologists use statistics but also what those numbers are presumed to represent.

Chapter 17 – Quiz

  • Chapter 17 – Flashcards

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  • Chapter 17 – Key Readings

    Boudewijnse, G.-J. A., Murray, D. J., & Bandomir, C. A. (2001). The fate of Herbart’s mathematical psychology. History of Psychology, 4(2), 107–132. https://doi.org/10.1037/1093-4510.4.2.107 

    Cowles, M. (2001). Statistics in Psychology: An historical perspective. Lawrence Erlbaum. 

    Crone, G., & Green, C. D. (2025). Tools of the data detective: A review of statistical methods to detect data and result anomalies in psychology. Theory & Psychology, 35(3), 359-380. https://doi.org/10.1177/09593543241311861 

    Danziger, K. (1990). Constructing the subject: Historical origins of psychological research. Cambridge University Press. 

    Friendly, M. and Denis, D. (2005), The early origins and development of the scatterplot. Journal of the History of the Behavioural Sciences, 41(2), 103-130. https://doi.org/10.1002/jhbs.20078 

    Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatty, J., & Krüger, L. (1989). The empire of chance: How probability changed science and everyday life. Cambridge University Press. 

    Lamiell, J. T. (2018). Re-centering psychology: From variables and statistics to persons and their stories. Theory & Psychology, 29(2), 282-284. https://doi.org/10.1177/0959354318766714 

    Lovie, S., & Lovie, P. (2004). A privileged and exemplar resource: Traumatic avoidance learning and the early triumph of mathematical psychology. History of Psychology, 7(3), 248–264. https://doi.org/10.1037/1093-4510.7.3.248 

    Lusinchi, D. (2022). Kiær and the rebirth of the representative method: A case-study in controversy management at the International Statistical Institute (1895–1903). Journal of the History of the Behavioral Sciences, 58(2), 163–182. https://doi.org/10.1002/jhbs.22145 

    Michell, J. (1997). Quantitative science and the definition of measurement in psychology. British Journal of Psychology, 88(3), 355–383. https://doi.org/10.1111/j.2044-8295.1997.tb02641.x 

    Morozova, S. V. (2022). How statistics became a “forbidden trick” for Soviet psychologists. History of Psychology, 25(2), 121–142. https://doi.org/10.1037/hop0000204 

    Salsburg, D. (2013). The lady tasting tea: How statistics revolutionized science in the twentieth century. Henry Holt and Company. 

    Uygun Tunç, D., Tunç, M. N., & Lakens, D. (2023). The epistemic and pragmatic function of dichotomous claims based on statistical hypothesis tests. Theory & Psychology, 33(3), 403-423. https://doi.org/10.1177/09593543231160112 

  • Chapter 17 – Reflective Questions

    1. What is reification, and why is it particularly relevant to the measurement of psychological constructs?
    2. How did statistical tools like the normal distribution and factor analysis influence the development of psychological theory and practice?
    3. In what ways did the work of figures like Galton and Fisher both advance and compromise the ethical standing of psychology?
    4. How does Joel Michell’s critique challenge the legitimacy of psychological measurement?
    5. How can recognising the role of reification help students become more critical consumers of psychological research today?

  • Chapter 17 – Weblinks

    Royal Statistical Society: Teaching Resources (Academic Resource)

    https://rss.org.uk

    This webpage is a hub of extensive and accessible information and case studies for learning about statistical literacy, including discussions of ethical issues and visualisation. This makes it an ideal resource for students who are new to concepts like statistical reasoning.

    The ASA Statement on p-Values (2016) (Academic Article)

    https://www.amstat.org/asa/files/pdfs/P-ValueStatement.pdf

    This position paper outlines the American Statistical Association’s concerns regarding misuse of statistical significance, with gives importance context for current ongoing debates in this field of study and research.

    Florence Nightingale Museum – Collections (Educational Resource)

    https://www.florence-nightingale.co.uk/collections/

    This website contains extensive information on the work and life of Florence Nightingale, with collections looking at her statistical innovations using coxcomb diagrams, linking to health dats and social reform.

    The Tea Lady Experiment – Numberphile (YouTube Video)

    https://www.youtube.com/watch?v=8ERFV7rV0vg

    This 17-minute video introduces and explains concepts like hypothesis testing and statistical measurement, and explains the Tea Tasting experiment using easy-to-understand visuals to explain these slightly more complex concepts to students who may be new to this aspect of statistics-based research.

    Understanding Uncertainty – Cambridge Mathematics Education Project (Educational Resource)

    http://understandinguncertainty.org

    This website presents lively explanations of concepts like probability and statistical reasoning, with many visual tools for students to engage with in order to give real-world context to these theories, bolstering their understanding of how to practically apply the information being presented.