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Trends and considerations in teaching introductory quantitative coursework in psychology doctoral programs.

Scholarship of Teaching and Learning in Psychology, Vol 12(1), Mar 2026, 18-29; doi:10.1037/stl0000399

Introductory quantitative training is ubiquitous in psychology graduate programs, yet there is limited information available on how instructors and departments structure these courses and what statistical skills are taught. We investigated the structure and content of the introductory quantitative training sequences from 23 PhD granting institutions that include schools from the Big Ten and top-rated psychology departments according to the U.S. News & World Report in 2022. Analyses revealed that all surveyed programs offered the introductory quantitative sequence within the department, and the majority of courses included a lab component and a graduate teaching assistant. The statistical program R was widely taught, while Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) were less frequently used. Most of the first-year graduate training focused on analysis of variance and regression analyses, which are foundational for more advanced quantitative methods. The inclusion of “new” statistical techniques and contemporary topics like effect sizes, confidence intervals, meta-analysis, power analysis, and open science and transparency practices varied across programs, though over 80% of programs incorporated at least one of the “new statistics” topics in their introductory quantitative sequence. We consider the implications of these findings for the instruction of quantitative courses in psychology undergraduate and graduate programs. (PsycInfo Database Record (c) 2026 APA, all rights reserved)

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Posted in: Journal Article Abstracts on 02/27/2026 | Link to this post on IFP |
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