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Samantha Mann; Aldert Vrij; Haneen Deeb – Applied Cognitive Psychology, 2024
We examined the efficacy of a Model Statement to detect opinion lies. A total of 93 participants discussed their opinion about the recent strikes on two occasions, 1 week apart. In one interview they told the truth and in the other interview they lied. Each interview consisted of two phases. In Phase 1 they discussed their alleged opinion (truth…
Descriptors: Opinions, Accuracy, Deception, Credibility
Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
Widaman, Keith F. – Educational and Psychological Measurement, 2023
The import or force of the result of a statistical test has long been portrayed as consistent with deductive reasoning. The simplest form of deductive argument has a first premise with conditional form, such as p[right arrow]q, which means that "if p is true, then q must be true." Given the first premise, one can either affirm or deny…
Descriptors: Hypothesis Testing, Statistical Analysis, Logical Thinking, Probability
Beth Chance; Karen McGaughey; Sophia Chung; Alex Goodman; Soma Roy; Nathan Tintle – Journal of Statistics and Data Science Education, 2025
"Simulation-based inference" is often considered a pedagogical strategy for helping students develop inferential reasoning, for example, giving them a visual and concrete reference for deciding whether the observed statistic is unlikely to happen by chance alone when the null hypothesis is true. In this article, we highlight for teachers…
Descriptors: Simulation, Sampling, Randomized Controlled Trials, Hypothesis Testing
Xiulin Kuang; Tessa H. S. Eysink; Ton de Jong – Journal of Research in Science Teaching, 2024
This study investigated the effects of presenting domain information (basic information about the domain) either together with or instead of offering exploratory practice (an exploratory opportunity in a simulation-based representation of the learning domain) prior to inquiry learning for facilitating students' hypothesis generation and subsequent…
Descriptors: Discovery Learning, Active Learning, Inquiry, Hypothesis Testing
Rosa W. Runhardt – Sociological Methods & Research, 2024
This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to…
Descriptors: Causal Models, Statistical Inference, Intervention, Investigations
Stephen Man-Kit Lee; Nicole Sin Hang Law; Shelley Xiuli Tong – Cognitive Science, 2024
Statistical learning enables humans to involuntarily process and utilize different kinds of patterns from the environment. However, the cognitive mechanisms underlying the simultaneous acquisition of multiple regularities from different perceptual modalities remain unclear. A novel multidimensional serial reaction time task was developed to test…
Descriptors: Statistics Education, Hypothesis Testing, Cognitive Processes, Reaction Time
Ritschard, Gilbert – Sociological Methods & Research, 2023
This study reviews and compares indicators that can serve to characterize numerically the nature of state sequences. It also introduces several new indicators. Alongside basic measures such as the length, the number of visited distinct states, and the number of state changes, we shall consider composite measures such as turbulence and the…
Descriptors: Comparative Analysis, Measurement Techniques, Hypothesis Testing, Foreign Countries
Nobuyuki Hanaki; Jan R. Magnus; Donghoon Yoo – Journal of Statistics and Data Science Education, 2023
Common sense is a dynamic concept and it is natural that our (statistical) common sense lags behind the development of statistical science. What is not so easy to understand is why common sense lags behind as much as it does. We conduct a survey among Japanese students and provide examples and tentative explanations of a number of statistical…
Descriptors: Statistics, Statistics Education, Epistemology, Statistical Analysis
Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
Tenko Raykov; Christine DiStefano; Natalja Menold – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…
Descriptors: Structural Equation Models, Hypothesis Testing, Longitudinal Studies, Research Methodology
Steffen Erickson – Society for Research on Educational Effectiveness, 2024
Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…
Descriptors: Structural Equation Models, Causal Models, Research Methodology, Error of Measurement
Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2022
Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes…
Descriptors: Bayesian Statistics, Hypothesis Testing, Mediation Theory, Vignettes
Feinstein, Osvaldo – American Journal of Evaluation, 2023
"Integrative evaluation" is an approach with two main phases: identification of plausible rival hypotheses and integration of rival hypotheses. The first phase may correspond to traditional adversary evaluation, whereas the second phase, that is not included in adversary evaluation, requires integrative thinking which can be applied when…
Descriptors: Evaluation, Integrated Activities, Intervention, Evaluators
Mandeep K. Dhami; Ian K. Belton; Peter De Werd; Velichka Hadzhieva; Lars Wicke – Cognitive Research: Principles and Implications, 2024
We empirically examined the effectiveness of how the Analysis of Competing Hypotheses (ACH) technique structures task information to help reduce confirmation bias (Study 1) and the portrayal of intelligence analysts as suffering from such bias (Study 2). Study 1 (N = 161) showed that individuals presented with hypotheses in rows and evidence items…
Descriptors: Task Analysis, Decision Making, Credibility, Cognitive Processes