KEY FEATURES: Wide interdisciplinary applicability with step-by-step examples drawn from a number of sciences and professional fields, including defense, medicine, education, and ecology, demonstrate the powerful application of information metrics to comparative case studies. Presentation of techniques that can be used broadly allows readers to apply what they learn in settings including business, finance, health care, environmental policy, security, and other settings where consequential decisions are made under conditions of uncertainty and complexity. Clear and accessible prose illustrated by concrete and carefully explained examples makes the methods easy to understand and immediately applicable. A concise review of the exciting intellectual foundations of information theory motivates student interest by linking research with critical real-world problems, from World War II cryptography to Cold War nuclear deterrence to solving modern cyber-security and strategic challenges. Appendices available both in the book and online provide a walkthrough of Excel or Google sheets for automating simple calculations, along with sample Excel sheets (Appendix A) and an implementation of the methods in the open source language, R (Appendix B).
Chapter 8: Conclusion
The Information Revolution was sparked by Claude Shannon’s articulation of a quantitative approach to understanding information. The underlying intuition was that all information could be conceptualized as discrete units, as bits, that with the appropriate channel size could be transmitted essentially without error. Neuroscientist and statistician Liam Paninski (2013) has called information theory “a pinnacle of statistical research … at once beautiful and applicable to a remarkably wide variety of questions” (p. 1191). Indeed, information theory has been applied across a range of fields and has proven a powerful tool for many different kinds of problems. In this book, we have demonstrated that Shannon’s insights about quantifying communication and measuring uncertainty and complexity are directly applicable to the challenges of rigorously and systematically ...