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Testing Tactile Masking between the Forearms

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Intuitive t tests: lay use of statistical information.

Natalie A Obrecht¹, Gretchen B Chapman, Rochel Gelman

¹Psychology Department, Rutgers University, Piscataway, New Jersey 08854-8020, USA. natalie@ruccs.rutgers.edu

Psychonomic Bulletin & Review

|January 31, 2008

Summary

People intuitively weigh mean product ratings most heavily in pairwise comparisons. Sample size and standard deviation (SD) received less consideration, even when raw data was provided, indicating a bias in statistical judgment.

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Area of Science:

Cognitive Psychology
Decision Making
Statistical Reasoning

Background:

Statistical pairwise comparisons typically rely on mean, standard deviation (SD), and sample size.
Understanding how individuals intuitively use these statistical components in judgment is crucial for cognitive science.
Prior research suggests potential biases in how laypeople interpret statistical information.

Purpose of the Study:

To investigate how individuals weigh different statistical factors (mean, sample size, SD) when comparing products.
To determine if providing raw data influences the utilization of sample size and SD in judgments.
To examine the normativity of intuitive statistical pairwise comparisons.

Main Methods:

203 undergraduates performed within-subjects comparisons of product pairs.
Manipulated average product ratings, number of raters (sample size), and SD of ratings.
Between-subjects manipulation involved providing summarized data versus summarized plus raw data.

Main Results:

Participants prioritized mean product ratings significantly over sample size and SD.
Sample size was weighted more than SD, but both were considerably less influential than the mean.
Access to raw data did not enhance the use of sample size or SD in decision-making.

Conclusions:

Intuitive product comparisons are heavily biased towards mean values, deviating from normative statistical principles.
Lay judgments underutilize crucial information like sample size and variability (SD).
Presenting raw data does not inherently correct for these biases in statistical interpretation.