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.
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.
Linear Models in the Mathematics of Uncertainty
265
Linear Models in the Mathematics of Uncertainty
265Paperback(2013)
Product Details
| ISBN-13: | 9783642438806 |
|---|---|
| Publisher: | Springer Berlin Heidelberg |
| Publication date: | 03/06/2015 |
| Series: | Studies in Computational Intelligence , #463 |
| Edition description: | 2013 |
| Pages: | 265 |
| Product dimensions: | 6.10(w) x 9.25(h) x 0.02(d) |