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Correlations and How to Interpret Them

Atmanspacher, Harald; Martin, Mike (2019). Correlations and How to Interpret Them. Information, 10(9):272.

Abstract

Correlations between observed data are at the heart of all empirical research that strives for establishing lawful regularities. However, there are numerous ways to assess these correlations, and there are numerous ways to make sense of them. This essay presents a bird’s eye perspective on different interpretive schemes to understand correlations. It is designed as a comparative survey of the basic concepts. Many important details to back it up can be found in the relevant technical literature. Correlations can (1) extend over time (diachronic correlations) or they can (2) relate data in an atemporal way (synchronic correlations). Within class (1), the standard interpretive accounts are based on causal models or on predictive models that are not necessarily causal. Examples within class (2) are (mainly unsupervised) data mining approaches, relations between domains (multiscale systems), nonlocal quantum correlations, and eventually correlations between the mental and the physical.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:150 Psychology
Scopus Subject Areas:Physical Sciences > Information Systems
Uncontrolled Keywords:Information Systems
Language:English
Date:29 August 2019
Deposited On:26 Sep 2019 12:47
Last Modified:22 Oct 2024 01:36
Publisher:MDPI Publishing
ISSN:2078-2489
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3390/info10090272
Project Information:
  • Funder: Collegium Helveticum
  • Grant ID: Semantic Analysis of multiscale Health Dynamics
  • Project Title:
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  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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