Understanding the Basics of Probability Theory and How it Applies to Advanced Technology

image Understanding the Basics of Probability Theory and How it Applies to Advanced Technology

People’s fascination with today’s technology usually stems from the high-end smartphones and the wide-ranging power they provide. In a way, modern advancements spurred the birth of a highly competitive market, featuring gadgets that encompass a gamut of areas in human inquiry. You have programs, or apps, on Tom’s Guide that predict the weather. Also, there are the likes of Spotify that provide music for free. Furthermore, there are those ultra-popular social media apps that eat up a lot of society’s time in the process. Basically, the sky is the limit when it comes to technology.

Whenever someone mentions the word “technology,” you can’t help but think of motherboards, holograms, and other – fictional or non-fictional – digital platforms. However, since the word also entails a certain degree of skill and expertise, technology reaches out to even the most unpredictable and mind-numbing area of mathematics: probability.

The theory of probability took the stage as early as the 17th century, when a couple of French mathematicians, namely Pierre de Fermat and Blaise Pascal, presented a discussion about problems focusing on games of chance. To put things in perspective, Wolfram Math World considers it a branch of mathematics, as it deals with calculating the prospect of a given event’s occurrence. For a further understanding of the subject, online gaming firm Pocketfruity even presents brain teasers that give you an insight into the concept of probability.

In its most basic practice, you can grasp the theory of probability in something as mundane as a coin toss. The chance that a coin drops in either heads or tails is just one, as there are no other options, supposing it lands clean flat. Measuring this problem is pretty much straightforward because it presents definite – not to mention plain – outcomes. However, it’s also important to recognize that each coin toss is an independent event; the result of a try has no impact on subsequent ones. It doesn’t matter how many consecutive times a coin faces heads; the next toss will always have a 50-50 chance of either going on the same side or shifting to tails. This so-called gambler’s fallacy has led to the agony and downfall of many gamers.

By probing deeper in the more complicated areas of technology, you’ll be able to see probability theory’s effect in computer programming – more specifically in the topics of machine learning, data-mining, and hashing. For instance, Jeremy Kun wrote about how the concepts of machine learning will forever be linked to the notion, as you’ll obtain and analyze various probabilistic learning algorithms. Also, the whole technological and mathematical process will be outlined by a bunch of arbitrary yet independently crucial variables.

All in all, modern day applications of the probability theory vary from the simplest of forms such as flipping a coin or picking up a random pair of socks in the drawer, to the more complicated ones in technology and computer programming. Having the basic knowledge of the subject doesn’t necessarily change your life, but in the long run, it’s better to carry this understanding if and when the need arises.

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