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Spatiotemporal Data Analysis$
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Gidon Eshel

Print publication date: 2011

Print ISBN-13: 9780691128917

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691128917.001.0001

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Introduction and Motivation

Introduction and Motivation

Chapter:
(p.1) One Introduction and Motivation
Source:
Spatiotemporal Data Analysis
Author(s):

Gidon Eshel

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691128917.003.0001

This chapter briefly sets out the reasons for analyzing data. The simplest need for data analysis arises most naturally in disciplines addressing phenomena that are, in all likelihood, inherently nondeterministic (e.g., feelings and psychology or stock market behavior). Since such fields of knowledge are not governed by known fundamental equations, the only way to generalize disparate observations into expanded knowledge is to analyze those observations. A more general rationale for analyzing data stems from the complementary relationship of empirical and theoretical science and dominates contexts and disciplines in which the studied phenomena have, at least in principle, fully knowable and usable fundamental governing dynamics. In these contexts, best exemplified by physics, theory and observations both vie for the helm.

Keywords:   data analysis, empiricism, nondeterministic phenomena, empirical science, theoretical science

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