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Related Concept Videos

Unusual Results01:16

Unusual Results

Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
Maximum unusual value = μ + 2σ
Minimum unusual value...
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...
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?
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Random Variables01:09

Random Variables

A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Errors In Hypothesis Tests01:14

Errors In Hypothesis Tests

When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.

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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Published on: September 19, 2012

Improbable outcomes: infrequent or extraordinary?

Karl Halvor Teigen1, Marie Juanchich, Anine H Riege

  • 1Department of Psychology, University of Oslo, Norway. k.h.teigen@psykologi.uio.no

Cognition
|February 5, 2013
PubMed
Summary

People perceive improbable events as having zero occurrence, not just low probability. This research redefines "improbable" outcomes as those beyond the expected range, challenging frequency-based interpretations.

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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Probability Theory

Background:

  • Previous research linked verbal probabilities like 'unlikely' to 10-30% numerical values.
  • A gap exists in understanding how people interpret 'improbable' outcomes beyond simple low frequencies.

Purpose of the Study:

  • To investigate the interpretation of 'improbable' outcomes using a new pragmatic methodology.
  • To determine if 'improbable' refers to low-frequency events or outcomes outside the expected range.

Main Methods:

  • Five studies were conducted involving participants completing or evaluating statements about improbable outcomes.
  • Methodology focused on outcome distributions and expected ranges, analyzing responses to quantitative and qualitative scenarios.

Main Results:

  • Participants consistently associated 'improbable' outcomes with a 0% frequency of occurrence.
  • Judgments of improbability favored extraordinary outcomes not present in the original sample or beyond observed ranges.
  • Examples included battery life, exam grades, and sea-level rise predictions.

Conclusions:

  • The interpretation of 'improbable' suggests outcomes beyond the expected range, not merely low-frequency events.
  • Findings support a causal (propensity) interpretation of probability over a statistical (frequency) one.