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Updated: Jan 16, 2026

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

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Published on: May 3, 2016

Children's understanding of conditional probabilities.

Jessica Crimston¹, Thomas Suddendorf¹, Jonathan Redshaw¹

¹School of Psychology, University of Queensland, Australia.

Journal of Experimental Child Psychology

|October 3, 2025

Summary

This study explored how children reason about conditional probabilities using a novel marble-tube task. Findings reveal that many children use heuristics instead of true probabilistic reasoning, highlighting variability in cognitive strategies.

Keywords:

Conditional probability Contingent probability Development Foresight Probability Uncertainty

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Published on: October 3, 2018

Area of Science:

Cognitive Development
Probability Theory
Developmental Psychology

Background:

Everyday decisions rely on conditional probabilities, yet research on children's understanding is limited.
Existing studies often focus on simple, single-cause probabilistic outcomes.

Purpose of the Study:

To introduce a new method for assessing children's conditional probability reasoning.
To investigate how 6- to 9-year-old children handle multi-step contingent probabilities.

Main Methods:

A novel task involving a marble navigating branching tubes was developed.
Assessed children's ability to account for multiple, contingent steps in probability estimation.
Minimal verbal demands and intuitive stimuli were utilized.

Main Results:

Children performed above chance, indicating some understanding of probability.
Correlational analyses suggested reliance on heuristics over conditional probabilistic reasoning for many participants.
Individual response patterns showed significant strategic variability.

Conclusions:

The developed task offers a new avenue for studying probabilistic reasoning across ages.
Highlights the need to differentiate heuristic strategies from genuine conditional probabilistic reasoning in children.
Suggests considerable diversity in how children approach complex probability tasks.