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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

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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.
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Reasoning01:30

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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.
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Natural and Artificial Concepts01:24

Natural and Artificial Concepts

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Collisions in Multiple Dimensions: Problem Solving01:06

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
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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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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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Similarity-based reasoning in conceptual spaces.

Igor Douven1, Steven Verheyen2, Shira Elqayam3

  • 1IHPST / CNRS / Panthéon-Sorbonne University, Paris, France.

Frontiers in Psychology
|September 21, 2023
PubMed
Summary
This summary is machine-generated.

This study formalizes similarity-based reasoning using mathematical similarity spaces. Findings show inference strength correlates with category distance in these spaces, supporting a novel formal model.

Keywords:
category-based inductionconceptual spacesinferencesimilaritysimilarity based reasoning

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Area of Science:

  • Cognitive Science
  • Philosophy of Mind
  • Mathematical Psychology

Background:

  • Deductive inference validity is tied to logical form.
  • Many pre-theoretically valid inferences lack formal deductive structure.
  • Similarity-based inferences, where conclusions are drawn from similar categories, require a formal framework.

Purpose of the Study:

  • To propose and test a formal model for similarity-based inferences.
  • To investigate the relationship between inference strength and similarity spaces.
  • To provide a quantitative measure for the validity of non-deductive reasoning.

Main Methods:

  • Development of a formal model where inference strength is a function of distance in a similarity space.
  • Empirical testing of the model through three experimental studies.
  • Utilizing mathematical spaces to represent human similarity judgments.

Main Results:

  • The proposed model, linking inference strength to distance in similarity spaces, was supported by empirical data.
  • Three studies consistently demonstrated the predictive power of the model.
  • Quantitative analysis confirmed the relationship between category distance and perceived inference strength.

Conclusions:

  • Similarity-based inferences can be formally treated using similarity spaces.
  • The strength of these inferences is quantifiable and predictable based on spatial distances.
  • This research offers a formal account for a significant class of non-deductive reasoning.