Let’s Talk about Stats: Revising Our Approach to Teaching Statistics in Psychology

Undergraduate statistics in psychology is an important, often challenging, course for students. The focus in psychology tends to be on hypothesis tests, such as t tests and analysis of variance. While adequate for some questions, there are many other topics we might include that could improve that data analytic abilities of students and improve psychological science in the long run. Topics such as generalized linear modeling, multilevel modeling, Bayesian statistics, model building and comparison, and causal analysis, could be introduced in an undergraduate psychological statistics course. For each topic, I discuss their importance and provide sources for instructor’s continuing education. These topics would give students greater flexibility in analyzing data, allow them to conduct more meaningful analyses, allow them to understand more modern data analytic approaches, and potentially help the field of psychology in the long run, by being one part of the strategy to address the reproducibility problem.

Statistics Instructors' Perceptions of Statistics Literacy in Different Undergraduate Programs

The present study aimed to investigate the statistical literacy perceptions of instructors who teach undergraduate statistics courses in different disciplines. Instructors were asked questions on their statistical literacy definitions, organization of the course content, topics emphasized or avoided by instructors in teaching statistics, and instructors post-course expectations from their students. Qualitative data gathered from interviews were analyzed and categorized under five main themes. The instructors' ultimate expectations from the students and the topics they emphasized during the courses are mostly stated in relation with statistical literacy. They provided less information related statistical literacy about two themes: course content and the issues they avoid. Recommendations from this study include reviewing and revising statistics course content and methods to reveal the components of statistical literacy.

New Statistics, Old Schools: An Overview of Current Introductory Undergraduate and Graduate Statistics Pedagogy Practices

Background A philosophical shift in statistics regarding emphasis on “New Statistics” (NS; Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 25(1), 7-29.) over conventional null hypothesis significance testing (NHST) raises the question of appropriate material coverage in undergraduate statistics courses. Objective We examined current practices in statistics pedagogy at the graduate and undergraduate levels for both NS and NHST. Method Using an online survey of a nationwide sample of current graduate students ( n = 452) and graduate faculty ( n = 162), we examined statistics pedagogy and perceptions of best approaches for teaching undergraduate statistics. Results In undergraduate statistics courses, coverage of NS material involves modest instruction in effect sizes and confidence intervals, while NHST remains dominant. Graduate courses have more balanced coverage. Effect size estimation was regarded as the most important NS knowledge for success in graduate school and the topic most in need of increased undergraduate coverage. Conclusion Undergraduate statistics courses could increase NS coverage, particularly effect size estimation, to better align with and prepare students for graduate work. Teaching Implications This research summarizes graduate program expectations and graduate student experiences regarding undergraduate statistics that current instructors can use to shape the content of their classes.

Teaching an Undergraduate Statistics Class in Digital Era

Nowadays technological developments are increasingly creative and tend to move towards digital. Technological developments have a major impact on the process of statistical learning at the University. In addition, many students lack understanding of statistical concepts and do not like statistical learning. In this paper, it is given a way of involving technology in the undergraduate class statistics teaching and what statistical concepts are needed in this digital age. Thus, it is hoped that the teaching of the undergraduate statistics class becomes something interesting and fun.