Year: 2014
Type: article
Abstract: Computing power and sophisticated data acquisition mask the fact that, in many sciences and engineering, the balance between theory and experiment is getting increasingly out of whack. The imbalance becomes an even greater concern in light of the increasingly complex natural systems science now confronts and the increasingly complex and interdependent sociotechnical systems modern engineering allows us to construct. Given its critical role in understanding such complex systems, Big Theory deserves a place alongside Big Data and Big Iron, says Jim Crutchfield. WIREs Comput Stat 2014, 6:75–79. doi: 10.1002/wics.1290 This article is categorized under: Software for Computational Statistics > Artificial Intelligence and Expert Systems Applications of Computational Statistics > Education in Computational Statistics
DOI: 10.1002/wics.1290
Author: James P. Crutchfield
Institution: University of California, Davis
Language: English
Subfield: History and Philosophy of Science
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W1527010484