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Linear Models in the Mathematics of Uncertainty
     

Linear Models in the Mathematics of Uncertainty

by John Mordeson, Mark Wierman, Terry D Clark, Alex Pham, Michael A. Redmond
 

The purpose of this book is to present new mathematical techniques for modeling global issues. These mathematical techniques are used to determine linear equations between a dependent variable and one or more independent variables in cases where standard techniques such as linear regression are not suitable.

In this book, we examine cases where the number of

Overview

The purpose of this book is to present new mathematical techniques for modeling global issues. These mathematical techniques are used to determine linear equations between a dependent variable and one or more independent variables in cases where standard techniques such as linear regression are not suitable.

In this book, we examine cases where the number of data points is small (effects of nuclear warfare), where the experiment is not repeatable (the breakup of the former Soviet Union), and where the data is derived from expert opinion (how conservative is a political party). In all these cases the data is difficult to measure and an assumption of randomness and/or statistical validity is questionable.

We apply our methods to real world issues in international relations such as nuclear deterrence, smart power, and cooperative threat reduction. We next apply our methods to issues in comparative politics such as successfuldemocratization, quality of life, economic freedom, political stability, and failed states. Finally, issues involving deaf and hard of hearing childrenare explored.

Product Details

ISBN-13:
9783642352232
Publisher:
Springer Berlin Heidelberg
Publication date:
02/28/2013
Series:
Studies in Computational Intelligence Series , #463
Edition description:
2013
Pages:
265
Product dimensions:
6.10(w) x 9.25(h) x 0.03(d)

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