Year: 2008
Type: article
Abstract: The ability to accurately infer relationships in our environment is critical to our survival.One factor influencing the detection and evaluation of population correlations is the size of the sample used in their assessment.There are three primary categories of tasks used to measure perceived correlation: rating, prediction, and frequency estimation.Several studies have investigated factors related to participants' subjective correlations, but few have included manipulations of sample size.The results of the present experiment demonstrated that the subjective correlations of participants who performed the frequency estimation or prediction task increased with information quantity.However, the opposite trend was found when participants judged moderately correlated populations in the rating task.In addition, simulations of artificial decision-makers demonstrated the possibility of extracting rules capable of accurately inferring population correlations which attenuates for the skewed nature of the sampling distribution of Pearson's r for small samples.
Author: Justin M. Gilkey
Institution: Bowling Green State University
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2601367191