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Related Concept Videos

Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Decision Making01:20

Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

The actual hypothesis testing begins by considering two hypotheses. They are termed  the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As  a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the population that is...
Framing Effects03:26

Framing Effects

Information is everywhere and its presentation—such as how and when items are presented—can impact our perceptions and decisions surrounding the info. This broad concept umbrellas framing effects—influences that occur due to the way information is framed in its appearance, whether it’s purely the order or the specific wording of a message. Let’s take a look at numerous ways in which two versions of something can objectively say the same thing, yet we respond in different ways based on the...

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Related Experiment Video

Updated: May 25, 2026

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance
13:20

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance

Published on: December 5, 2025

Context effects in multi-alternative decision making: empirical data and a Bayesian model.

Guy Hawkins1, Scott D Brown, Mark Steyvers

  • 1School of Psychology, University of Newcastle, Callaghan, NSW, Australia. guy.hawkins@newcastle.au

Cognitive Science
|January 20, 2012
PubMed
Summary
This summary is machine-generated.

Response time follows Hick's Law, but error rates in decision-making are largely independent of the number of choices. An optimal observer model better explains both response time and error rate data.

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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Related Experiment Videos

Last Updated: May 25, 2026

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance
13:20

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance

Published on: December 5, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Area of Science:

  • Cognitive Psychology
  • Human Decision-Making
  • Information Processing

Background:

  • Hick's Law describes how response time increases with the number of choice alternatives.
  • Previous research shows inconsistent findings regarding error rates in multi-alternative choice tasks.
  • Existing models struggle to consistently explain both response time and error rate data.

Purpose of the Study:

  • To investigate the relationship between the number of choice alternatives and error rates in decision-making.
  • To re-evaluate the validity of using error rate data to test theories of Hick's Law.
  • To explore alternative models that can account for both response time and error rate patterns.

Main Methods:

  • Conducted two experiments examining decision-making with varying numbers of choice alternatives.
  • Analyzed response times and error rates across different experimental conditions.
  • Compared empirical data against predictions from established and alternative theoretical models.

Main Results:

  • Error rates were found to be largely independent of the number of choice alternatives.
  • Context effects can influence participants to trade speed for accuracy, affecting error rates.
  • Previous conclusions drawn from error rate data to discriminate between Hick's Law theories are questioned.

Conclusions:

  • Error rates in multi-alternative choice are robustly independent of choice set size, contrary to some prior interpretations.
  • An optimal observer model, approximating Bayesian inference, offers a parsimonious explanation for both response time and error rate data.
  • Perceptual limitations may account for deviations from ideal Bayesian inference in human decision-making.