Related Experiment Video

Updated: Jun 4, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

Implicit causality bias in English: a corpus of 300 verbs

Evelyn C Ferstl1, Alan Garnham, Christina Manouilidou

  • 1University of Sussex, School of Psychology, Falmer, Brighton, BN1 9QH, UK. e.c.ferstl@sussex.ac.uk

Behavior Research Methods
|February 3, 2011
PubMed

More Related Videos

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects07:36

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

Published on: November 30, 2018

Using the Visual World Paradigm to Study Sentence Comprehension in Mandarin-Speaking Children with Autism06:15

Using the Visual World Paradigm to Study Sentence Comprehension in Mandarin-Speaking Children with Autism

Published on: October 3, 2018

Related Concept Videos

Criteria for Causality: Bradford Hill Criteria - II01:28

Criteria for Causality: Bradford Hill Criteria - II

The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
Criteria for Causality: Bradford Hill Criteria - I01:30

Criteria for Causality: Bradford Hill Criteria - I

The Bradford Hill criteria are a group of principles that provide a framework to determine a causal relationship between a specific factor and a disease. There are nine criteria that are pivotal in assessing causality in epidemiological studies. Here's a closer look at Strength, Consistency, Specificity, and Temporality criteria with definitions and examples:
Correlation and Causation01:27

Correlation and Causation

Correlation and CausationStatistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. A relationship between variables shows correlation, but it does not show cause-and-effect. A direct cause-and-effect relationship requires additional controlled experiments. If no consistent relationship exists between the variables, then there is no correlation.Correlation versus CausationIf the dependent variable increases or decreases when the...
Cause and Effect01:53

Cause and Effect

While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
Correspondence Bias01:17

Correspondence Bias

Correspondence bias, also referred to as the fundamental attribution error, describes the tendency to attribute another person’s behavior to internal characteristics rather than situational influences. This cognitive bias leads individuals to overlook external factors that may be influencing actions, thereby fostering potentially inaccurate assessments of others’ intentions and dispositions.Empirical Evidence for Correspondence BiasResearch has consistently demonstrated the prevalence of...
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...