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Related Concept Videos

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: 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...
The Availability Heuristic01:08

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
Probability in Statistics01:14

Probability in Statistics

Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
Purposive Learning01:22

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a bonus...
First Impression01:09

First Impression

First impressions play a crucial role in social perception, shaping how individuals assess others in professional, academic, and interpersonal contexts. Psychological research highlights the significance of cognitive biases, such as the primacy and recency effects, which influence how people interpret and recall information.The Primacy Effect and Cognitive AnchoringThe primacy effect describes the tendency for initial information to impact judgment disproportionately. When individuals encounter...

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Related Experiment Video

Updated: Jun 12, 2026

Acquisition of a High-precision Skilled Forelimb Reaching Task in Rats
08:59

Acquisition of a High-precision Skilled Forelimb Reaching Task in Rats

Published on: June 22, 2015

Experience matters: information acquisition optimizes probability gain.

Jonathan D Nelson1, Craig R M McKenzie, Garrison W Cottrell

  • 1Max Planck Institute for Human Development, Berlin, Germany. jnelson@salk.edu

Psychological Science
|June 8, 2010
PubMed
Summary
This summary is machine-generated.

Humans prioritize probability gain when seeking information, especially through experience-based learning. This finding is robust across different learning methods, suggesting probability gain is a key driver of information acquisition.

Related Experiment Videos

Last Updated: Jun 12, 2026

Acquisition of a High-precision Skilled Forelimb Reaching Task in Rats
08:59

Acquisition of a High-precision Skilled Forelimb Reaching Task in Rats

Published on: June 22, 2015

Area of Science:

  • Cognitive Science
  • Decision Science
  • Information Theory

Background:

  • Information acquisition is crucial for various cognitive processes, including perception, diagnosis, and inference.
  • Several statistical theories, such as information gain and probability gain, attempt to model the value of information.
  • Previous research indicates these theories are consistent with existing human information acquisition data.

Purpose of the Study:

  • To experimentally determine which statistical theory best describes human information search behavior.
  • To compare the predictive power of information gain, Kullback-Liebler distance, probability gain, and impact theories.
  • To investigate the influence of learning methods on information search strategies.

Main Methods:

  • Three computer-optimized experiments were conducted to maximize informative outcomes.
  • Natural sampling and experience-based learning were used to convey environmental probabilities in Experiment 1.
  • Verbal summary statistics were employed in Experiments 1 and 2 to contrast with experience-based learning.

Main Results:

  • Probability gain significantly outperformed other statistical theories and heuristics in explaining information search behavior in experience-based learning.
  • Human search behavior differed when probabilities were conveyed via summary statistics versus experience-based learning.
  • Experiment 3 confirmed the robustness of probability gain preference, indicating minimal contribution from other models.

Conclusions:

  • Probability gain is a dominant factor in human information search, particularly when learning from experience.
  • The method of conveying information influences how individuals search for it.
  • This study refines our understanding of the cognitive mechanisms underlying information value assessment.