Related Experiment Video
Updated: Aug 12, 2026

A Tactile Automated Passive-Finger Stimulator (TAPS)
Published on: June 3, 2009
Children's probability intuitions: understanding the expected value of complex gambles
1Department of Psychology, University College London, UK. a.schlottmann@psychol.ucl.ac.uk
Children as young as six demonstrate a sophisticated understanding of probability and expected value, using multiplication rules earlier than typically observed. This research challenges traditional views on children's cognitive abilities in mathematical reasoning.
Area of Science:
- Cognitive Development
- Developmental Psychology
- Decision Science
Background:
- Traditional views suggest children develop multiplicative reasoning later in childhood.
- Understanding expected value is crucial for decision-making, but its development in children is not fully understood.
Purpose of the Study:
- To investigate how children integrate probability and value to judge expected value in complex gambles.
- To examine the age at which children grasp abstract concepts of probability and expected value.
Main Methods:
- Information Integration Theory was applied in two experiments with 6-year-olds, 9-year-olds, and adults.
- Participants judged the expected value of chance games with varying probabilities and prize values.
Main Results:
- All age groups correctly applied the multiplication rule for integrating probability and value.
- Participants demonstrated understanding of both outcomes but showed individual differences in risk attitudes.
- Even young children treated probability as an abstract concept.
Conclusions:
- Children as young as 5-6 years old possess a functional understanding of probability and expected value.
- Cognitive intuition supports precocious performance but can also lead to biases in judgment.
- Findings challenge traditional timelines for multiplicative reasoning development.
More Related Videos
13:04Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
08:24The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
Related Concept Videos
Probability Laws
Probability in Statistics
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...
Probability Distributions
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson probability...
Expected Value
Binomial Probability Distribution
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...