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Related Concept Videos

Deductive Reasoning01:16

Deductive Reasoning

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Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
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Inductive Reasoning00:59

Inductive Reasoning

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Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
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Reasoning01:30

Reasoning

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Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
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Bias01:22

Bias

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
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Hindsight Biases01:12

Hindsight Biases

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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? 
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Confirmation Biases01:31

Confirmation Biases

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The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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Toward a General Framework of Biased Reasoning: Coherence-Based Reasoning.

Dan Simon1,2, Stephen J Read2

  • 1Gould School of Law, University of Southern California.

Perspectives on Psychological Science : a Journal of the Association for Psychological Science
|November 20, 2023
PubMed
Summary

Coherence-based reasoning offers a unified framework for understanding cognitive biases. This adaptive mental process can lead to errors when internal networks are flawed, explaining various reasoning deviations.

Keywords:
affectautomatic processingbiascognitioncoherence-based reasoningdecision-makingemotiongoalsjudgmentmotivationreasoningrewardsocial cognitionthinkingunconscious

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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Behavioral Economics

Background:

  • Existing research on cognitive biases is extensive but fragmented and lacks a unifying theory.
  • Understanding deviations from normative reasoning is crucial for cognitive science.

Purpose of the Study:

  • To propose coherence-based reasoning as a parsimonious theoretical framework for explaining cognitive biases.
  • To integrate diverse findings in bias research under a single, coherent model.

Main Methods:

  • Conceptual framework development based on connectionist networks and constraint-satisfaction processing.
  • Application of the framework to explain established biases such as confirmation bias, halo effect, and motivated reasoning.

Main Results:

  • Coherence-based reasoning provides an adaptive mental apparatus that can be disrupted by non-normative network elements.
  • The framework successfully accounts for a wide range of biased reasoning phenomena.

Conclusions:

  • Coherence-based reasoning offers a unified and parsimonious explanation for numerous cognitive biases.
  • This framework highlights how adaptive cognitive processes can become sources of systematic error.