Psychology teachers have likely heard about the "replication crisis" and the "open science movement" in psychology, and they are probably aware that psychologists have proposed new standards for research practice. How should our psychology courses reflect these new standards? We describe several modern practices that have…

Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…

This study describes a close replication of Friedrich, Buday, and Kerr's late 1990s survey of statistics instruction in undergraduate psychology programs. Disciplinary reform efforts at that time such as the report of the APA Task Force on Statistical Inference, together with recent progress in the "new statistics" movement, raise…

We describe how students can be encouraged to actively review course contents on inferential statistics by creating application-oriented exercises and sample solutions on the basis of concrete and realistic research articles and their data. For evaluation purposes, we use students' reactions to the activity and investigate its effects on the final…

Three different bootstrap methods for estimating confidence intervals (CIs) for coefficient alpha were investigated. In addition, the bootstrap methods were compared with the most promising coefficient alpha CI estimation methods reported in the literature. The CI methods were assessed through a Monte Carlo simulation utilizing conditions…

In this article, we discuss a collection of active learning activities derived from classic psychology studies that illustrate the appropriate use of descriptive and inferential statistics. (Contains 2 tables.)

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy…

A model-based framework, due originally to R. A. Fisher, and a design-based framework, due originally to J. Neyman, offer alternative mechanisms for inference from samples to populations. We show how these frameworks can utilize different types of samples (nonrandom or random vs. only random) and allow different kinds of inference (descriptive vs.…

According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…

Computerized lessons employing stimulus equivalence technology, used previously under laboratory conditions to teach inferential statistics concepts to college students, were employed in a group setting for the first time. Students showed the same directly taught and emergent learning gains as in laboratory studies. A brief paper-and-pencil…

Educators in large-enrollment courses are faced with the challenge of effectively disseminating information to their students to ensure that they learn the content provided. A related issue involves the means by which instructors evaluate student performance. Offering effective forms of performance feedback may be one technique to provide students…

The experimental analysis of behavior began as an inductively oriented, empirically based scientific field. As the field grew, its distinctive system of science--radical behaviorism--grew with it. The continuing growth of the empirical base of the field has been accompanied by the growth of the literature on radical behaviorism and its…

A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of "state classification" to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They…

D. Trafimow presented an analysis of null hypothesis significance testing (NHST) using Bayes's theorem. Among other points, he concluded that NHST is logically invalid, but that logically valid Bayesian analyses are often not possible. The latter conclusion reflects a fundamental misunderstanding of the nature of Bayesian inference. This view…

This paper comments on the response offered by Trafimow on Lee and Wagenmakers comments on Trafimow's original article. It seems our comment should have made it clear that the objective Bayesian approach we advocate views probabilities neither as relative frequencies nor as belief states, but as degrees of plausibility assigned to propositions in…