Seven (indeed, plus or minus two) and the detection of correlations
Related Experiment Video
Updated: Oct 16, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
1Goldie Rotman Center for Cognitive Science and Education, School of Education, Hebrew University of Jerusalem, Israel. kareev@vms.huji.ac.il
Abstract:
Capacity limitations of working memory force people to rely on samples consisting of 7 +/- 2 items. The implications of these limitations for the early detection of correlations between binary variables were explored in a theoretical analysis of the sampling distribution of phi, the contingency coefficient. The analysis indicated that, for strong correlations (phi > .50), sample sizes of 7 +/- 2 are most likely to produce a sample correlation that is more extreme than that of the population. Another analysis then revealed that there is a similar cutoff point at which useful correlations (i.e., for which each variable is a valid predictor of the other) first outnumber correlations for which this is not the case. Capacity limitations are thus shown to maximize the chances for the early detection of strong and useful relations.
More Related Videos
07:28Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level
Published on: January 24, 2025
04:35Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Related Concept Videos
Calibration Curves: Correlation Coefficient
Correlations
Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...
Correlation and Regression
Correlation of Experimental Data
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity, and...
Spearman's Rank Correlation Test
Spearman's test calculates correlation by...