Bibliograph

Linear Models in the Mathematics of Uncertainty, by John N. Mordeson, Mark J. Wierman, Terry D. Clark, Alex Pham, Michael A. Redmond

Type

Label

Linear Models in the Mathematics of Uncertainty, by John N. Mordeson, Mark J. Wierman, Terry D. Clark, Alex Pham, Michael A. Redmond

Language

eng

resource.imageBitDepth

Literary Form

non fiction

Main title

Linear Models in the Mathematics of Uncertainty

Medium

electronic resource

Oclc number

827276208

Responsibility statement

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

Series statement

Springer eBooks.

Summary

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 successful democratization, quality of life, economic freedom, political stability, and failed states. Finally, issues involving deaf and hard of hearing children are explored.

Table Of Contents

Part I Mathematics Of Uncertainty -- Part II The Problems -- Part III Applications -- Part IV Analysis of Results

Contributor

Creator