Making Heads or Tails of RMS Measurements

Your Gaussian Guide Although it goes by many names, the Gaussian function appears everywhere in statistics. In this article, Robert takes a look at the math of the Gaussian function in the context of coin-toss data analysis. He then shows why this is significant in electronics, by linking the function to RMS (root mean square) measurements. Topics Discussed How to understand the Gaussian function and how it relates to root means squared (RMS)What is the Bernoulli Trial and its connection to coin tossingHow does Pascal’s triangle work?How to use Scilab’s random generator functionHow to undertand  name: Root Mean Square (RMS) or coupled RMS.  Tech Used Scilab toolTeledyne LeCroy Waverunner 610Zi Welcome back to "The Darker Side." I am writing this article in April 2020, in the middle of the COVID-19 crisis from my home in France. Like hundreds of millions of people, I have been locked-down in my home for one month and will be for at least a couple more months. Not sure if we are already in the middle of it, but I hope that you are all safe, and that the worldwide situation will have improved when you read this article. Anyway, I am spending a lot of time reading articles full of medical statistics—trying to balance actual facts and the effects of randomness. That's what gave me the idea for this article. This month I will bring you into the world of statistics. More precisely, my goal is to show you why the so-called Gaussian function appears everywhere. If you have already seen expressions like “normal distribution” or “bell curve,” this is exactly the same thing. In fact, this ubiquitous notion has several names. Because we are electronics addicts, I'll show you why this notion is closely linked with RMS (root mean square) measurements. HEADS OR TAILS? Let’s start with the most basic random game: Tossing a coin (Figure 1). As you probably know, this is a very old method to invoke randomness. Even the Romans