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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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Statistics in Deterministic Sciences: An Introduction

Statistics in Deterministic Sciences: An Introduction

(p.96) Seven Statistics in Deterministic Sciences: An Introduction
Spatiotemporal Data Analysis

Gidon Eshel

Princeton University Press

This chapter focuses on the relevance of statistics in deterministic science. While most physical phenomena of concern to natural sciences are governed by fundamental, mostly known, physics, their application to such complex systems as the ocean, atmosphere, or ecosystems is monumentally difficult. For most such systems, the full problems—the values of all relevant variables at all space and time locations—are essentially intractable, even with the fastest computers. Hence, there is always more to the focus of inquiry that cannot be modeled; we must somehow fill in the gaps. This is where statistics come in. Until the state of the physical system under investigation is fully quantified (i.e., until the value of every dynamical variable is perfectly known at every point in space and time), there is a certain amount of indeterminacy in every statement made about the state of the system. The remainder of the chapter discusses probability distributions and degrees of freedom.

Keywords:   data analysis, statistics, deterministic science, probability distribution, degrees of freedom

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