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Related Concept Videos

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...
Reason and Intuition01:37

Reason and Intuition

The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the brain can only use...
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000...
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor 't,' or...
Hindsight Biases01:12

Hindsight Biases

Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
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...

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Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
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Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Decision making and confidence given uncertain advice.

Michael D Lee1, Matthew J Dry

  • 1Department of Cognitive Sciences, University of California, IrvineSchool of Psychology, University of Adelaide.

Cognitive Science
|June 28, 2011
PubMed
Summary
This summary is machine-generated.

Human decision-making confidence depends on both advice frequency and accuracy, not just accuracy. Confidence also decreases with more required decisions, as shown by a new self-regulating accumulator model.

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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Computational Neuroscience

Background:

  • Human decision-making is influenced by external advice.
  • Understanding subjective confidence is crucial for modeling human reasoning.

Purpose of the Study:

  • To investigate how information frequency and accuracy affect decision-making and confidence.
  • To develop and validate a computational model for human decision-making and confidence.

Main Methods:

  • A forced-choice task manipulating advice frequency and accuracy.
  • Empirical data collection on decisions and subjective confidence.
  • Development and evaluation of a self-regulating accumulator model.

Main Results:

  • Decision-making aligned with provided advice.
  • Subjective confidence influenced by both advice frequency and accuracy.
  • Reduced confidence in decisions when more guesses were required.

Conclusions:

  • The self-regulating accumulator model accurately captures human decision-making and confidence.
  • Model complexity is not the reason for its data-fitting ability.
  • Insights into human reasoning under uncertainty were gained.