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Related Concept Videos

Decision Making01:20

Decision Making

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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...
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Decision Making: Traditional Method01:14

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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.
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Decision Making: P-value Method01:09

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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...
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Reason and Intuition01:37

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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...
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Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
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Study Design in Statistics01:15

Study Design in Statistics

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A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
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Is it Reasonable to Study Decision-Making Quantitatively?

Richard M Shiffrin1

  • 1Department of Brain and Psychological Sciences, Indiana University.

Topics in Cognitive Science
|May 29, 2021
PubMed
Summary
This summary is machine-generated.

Human decision-making often involves vague information, challenging quantitative models. This research explores how people make choices with qualitative data, a common real-world scenario.

Keywords:
Decision-makingQualitative versus quantitativeVagueness

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Area of Science:

  • Decision Science
  • Cognitive Psychology
  • Behavioral Economics

Background:

  • Decision-making research often uses quantitative models with precise values and probabilities.
  • Alternative approaches examine choices with qualitative or vague information.
  • Some research models verbal choices using verbal heuristics.

Purpose of the Study:

  • To assess the relevance of quantitative decision-making models for real-world choices.
  • To explore how humans make decisions with vague or qualitative information.
  • To address the limitations of quantitative approaches in uncertain environments.

Main Methods:

  • Analysis of existing decision-making research paradigms.
  • Conceptual exploration of quantitative versus qualitative decision-making.
  • Illustrative example of high uncertainty impacting quantitative models.

Main Results:

  • Quantitative models may struggle when values and probabilities are vague or qualitative.
  • Humans possess evolved capabilities for decision-making in uncertain, qualitative settings.
  • The applicability of quantitative research depends on its ability to approximate natural decision-making.

Conclusions:

  • Traditional quantitative decision science may not fully capture real-world decision-making.
  • Understanding qualitative decision-making is crucial for a comprehensive view.
  • Further research is needed to bridge the gap between quantitative models and natural human choices.