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Quantitative psychology

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Title: Quantitative psychology  
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Subject: Basic science (psychology), Abnormal psychology, Mathematical psychology, Psychology, Quantitative research
Collection: Branches of Psychology, Psychometrics, Quantitative Analysis of Behavior, Quantitative Research
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Quantitative psychology

Quantitative psychology is a field of scientific study that focuses on the mathematical modeling, research design and methodology, and statistical analysis of human attributes and psychological processes.[1] Quantitative psychologists research traditional and novel methods of psychometrics, a field of study concerned with the theory and technique of psychological measurement.[2] At a general level, quantitative psychologists help create methods for all psychologists to test their hypotheses.

Psychological research has a long history of contributing to statistical applications and theory. Today, quantitative psychology is recognized as its own branch of psychology by the American Psychological Association (APA), with doctoral degree programs awarded in this specialization in some universities in Europe and North America. Quantitative psychologists have traditionally been in high demand in industry, government, and academia. Their combined training in both social science and quantitative methodology provides a unique skill set for solving both applied and theoretical problems in a variety of areas.


  • History 1
    • Intelligence testing 1.1
    • Statistical techniques 1.2
    • Criticism 1.3
  • Education and training 2
    • Undergraduate 2.1
    • Graduate 2.2
      • Shortage of qualified applicants 2.2.1
  • Research areas 3
  • Professional organizations 4
  • Notable people 5
  • See also 6
  • References 7
  • Further reading 8
  • External links 9


Francis Galton's correlation diagram, 1875.

Quantitative psychology has its roots in early experimental psychology when the scientific method was first applied to psychological phenomena. Gustav Fechner, Wilhelm Wundt, and Hermann von Helmholtz are recognized as some of the founders of modern experimental psychology. In particular, Fechner demonstrated that because the mind was susceptible to measurement and mathematical treatment, psychology had the potential to become a quantified science. Theorists such as Immanuel Kant had previously stated that this was impossible, and that therefore, a science of psychology was also impossible.

Intelligence testing

Quantitative psychology as a discipline has a history in mental testing, especially intelligence testing, and behavioral measurement. The English statistician Francis Galton made the first attempt at creating a standardized test for rating a person's intelligence. A pioneer of psychometrics and the application of statistical methods to the study of human diversity and the study of inheritance of human traits, he believed that intelligence was largely a product of heredity.[3] He hypothesized that there should exist a correlation between intelligence and other desirable traits like good reflexes, muscle grip, and head size.[4] He set up the first mental testing centre in the world in 1882 and he published "Inquiries into Human Faculty and Its Development" in 1883, in which he set out his theories.

Statistical techniques

IQ scores represented by a normal distribution.

The most common mathematical techniques used by psychologists come from statistics. Classical statistics include the z-test and the binomial test. Pearson introduced the correlation coefficient and the chi-squared test. The 1900-1920 period saw the t-test (Student, 1908), the ANOVA (Fischer, 1925) and a non-parametric correlation coefficient (Spearman, 1904). However, a considerably larger number of tests were developed past 1965 (e.g., all the multivariate tests). Popular techniques (such as Hierarchical Linear Model, Arnold, 1992, Structural Equation Modeling, Byrne, 1996 and Independent Component Analysis, Hyvarinën, Karhunen and Oja, 2001) all have less than 20 years of existence.[5]

In 1946, psychologist Stanley Smith Stevens introduced a theory of levels of measurement in a paper that is often used by statisticians today.[6] The levels of measurement he proposed were Nominal, Ordinal, Ratio, and Interval.

While a New York University professor of psychology, Jacob Cohen researched quantitative methods involving statistical power and effect size, which helped to lay foundations for current statistical meta-analysis and the methods of estimation statistics.[7] He gave his name to Cohen's kappa and Cohen's d.

In 1990, an influential paper titled "Graduate Training in Statistics, Methodology, and Measurement in Psychology" was published in the American Psychologist journal. This article discussed the need for increased and up-to-date training in quantitative methods for psychology graduate programs in the United States.[8]


There have been critiques about the use of quantitative methods in psychological research. Notably, Professor Joel Michell from the University of Sydney has written extensively on the use and misuse of psychometric techniques.

Education and training


Training for quantitative psychology can begin informally at the undergraduate level. Many graduate schools recommend that students have some coursework in psychology and complete the full college sequence of calculus (including multivariate calculus) and a course in linear algebra. Quantitative coursework in other fields such as economics and research methods and statistics courses for psychology majors are also helpful. Historically, however, students without all these courses have been accepted if other aspects of their application show promise. Some schools also offer formal minors in areas related to quantitative psychology. For example, the University of Kansas offers a minor in "Social and Behavioral Sciences Methodology" that provides advanced training in research methodology, applied data analysis, and practical research experience relevant to quantitative psychology.[9] Coursework in computer science is also useful. Mastery of an object-oriented programming language or learning to write code in SPSS or R is useful for the type of data analysis performed in graduate school.


Peabody College (pictured) at Vanderbilt University houses their Quantitative Methods program.

Quantitative psychologists may possess a doctoral degree or a master's degree. Due to its interdisciplinary nature and depending on the research focus of the university, these programs may be housed in a school's college of education or in their psychology department. Programs that focus especially in educational research and psychometrics are often part of education or educational psychology departments. These programs may therefore have different names mentioning "research methods" or "quantitative methods", such as the "Research and Evaluation Methodology" Ph.D. from the University of Florida or the "Quantitative Methods" degree at the University of Pennsylvania. However, some universities may have separate programs in their two colleges. For example, the University of Washington has a "Quantitative psychology" degree in their psychology department and a separate "Measurement & Statistics" Ph.D. in their college of education. Others, such as Vanderbilt University's Ph.D in Psychological Sciences is jointly housed across its two psychology departments.

Universities with a mathematical focus include McGill University's "Quantitative Psychology and Modeling" program and Purdue University's "Mathematical and Computational Cognitive Science" degrees. Students with an interest in modeling biological or functional data may go into related fields such as biostatistics or computational neuroscience.

Doctoral programs typical accept students with only bachelor's degrees, although some schools may require a master's degree before applying. After the first two years of studies, graduate students typically earn a Masters of Art in Psychology, Masters of Science in Statistics or Applied statistics, or both.

Additionally, several universities offer minor concentrations in quantitative methods, such as New York University.

Companies that produce standardized tests such as College Board, Educational Testing Service, and American College Testing are some of the biggest private sector employers of quantitative psychologists. These companies also often provide internships to students in graduate school.

Shortage of qualified applicants

In August 2005, the American Psychological Association expressed the need for more quantitative psychologists in the industry—for every PhD awarded in the subject, there were about 2.5 quantitative psychologist position openings.[10] Due to a lack of applicants in the field, the APA created a Task Force to study the state of quantitative psychology and predict its future. Domestic U.S. applicants are especially lacking. The majority of international applicants come from Asian countries, especially South Korea and China.[11] In response to the lack of qualified applicants, the APA Council of Representatives authorized a special task force in 2006.[12] The task force was chaired by Leona S. Aiken from Arizona State University.

Research areas

Example of a social network diagram.

Quantitative psychologists generally have a main area of interest.[13] Notable research areas in psychometrics include item response theory and computer adaptive testing, which focus on education and intelligence testing. Other research areas include modeling psychological processes through time series analysis, such as in fMRI data collection, and structural equation modeling, social network analysis, human decision science, and statistical genetics.

Two common types of psychometric tests are: aptitude tests, which are supposed to measure raw intellectual ability, and personality tests that aim to assess your character, temperament, and how you deal with problems.

Item response theory is based on the application of related mathematical models to testing data. Because it is generally regarded as superior to classical test theory, it is the preferred method for developing scales in the United States, especially when optimal decisions are demanded, as in so-called high-stakes tests, e.g., the Graduate Record Examination (GRE) and Graduate Management Admission Test (GMAT).

Professional organizations

Quantitative psychology is served by several scientific organizations. These include the Psychometric Society, Division 5 of the American Psychological Association (Evaluation, Measurement and Statistics), the Society of Multivariate Experimental Psychology, and the European Society for Methodology. Associated disciplines include statistics, mathematics, educational measurement, educational statistics, sociology, and political science. Several scholarly journals reflect the efforts of scientists in these areas, notably Psychometrika, Multivariate Behavioral Research, Structural Equation Modeling and Psychological Methods.

Notable people

The following is a select list of quantitative psychologists or people who have contributed to the field:

See also


  1. ^
  2. ^
  3. ^ Bulmer, M. (1999). The development of Francis Galton's ideas on the mechanism of heredity. Journal of the History of Biology, 32(3), 263-292. Cowan, R. S. (1972). Francis Galton's contribution to genetics. Journal of the History of Biology, 5(2), 389-412. See also Burbridge, D. (2001). Francis Galton on twins, heredity and social class. British Journal for the History of Science, 34(3), 323-340.
  4. ^ Fancher, R. E. (1983). Biographical origins of Francis Galton's psychology. Isis, 74(2), 227-233.
  5. ^
  6. ^
  7. ^ Cohen's entry in Encyclopedia of Statistics in Behavioral Science
  8. ^
  9. ^
  10. ^ Report of the Task Force for Increasing the Number of Quantitative Psychologists, page 1. American Psychological Association. Retrieved February 15, 2012
  11. ^
  12. ^
  13. ^

Further reading

External links

  • APA Division 5: Evaluation, Measurement and Statistics
  • The Psychometric Society
  • The Society of Multivariate Experimental Psychology
  • The European Society for Methodology
  • Society for Mathematical Psychology
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