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Introduction

Michael Taillard

A chapter in Analytics and Modern Warfare, 2014, pp 1-5 from Palgrave Macmillan

Abstract: Abstract Analytics tend to look pretty scary, and the thought of deciphering a book of mathematical principles with which you are not familiar can be extremely intimidating. Some people claim that they would prefer to face an entire army of insurgents than a single statistics examination, but if you are a big sports fan, then odds are good you have used applied statistical analytics already! For example, if you watch baseball it is likely that you have followed the performance of a particular player, tracking the number of games in which they have played, the number of times per game they successfully hit the ball or reach a particular base, the number of times per game they scored a point, hit a homerun, stolen base, and so forth. You may have even used the averages between these games to estimate what their performance will be in a future game, and try to predict which team will win a game or make it to the championship. You may have even applied this information to infer what a team’s strengths are, and what they need to work on in order to be competitive during the rest of the season. Casinos are also an extremely common place where people frequently utilized applied analytics, in the form of probability theory. Calculating the odds of an outcome on any game is relatively simple once you know the basics, and that will help you improve your successes by determining the amount of “house advantage” (the degree to which a casino maintains a higher probability of winning than the player) inherent in each game, how to make individual bets, and how to develop multi-bet strategies.

Keywords: Mathematical Principle; Information Warfare; Modern Warfare; Coincident Indicator; Quality Management Technique (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-1-137-40787-0_1

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DOI: 10.1057/9781137407870_1

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