Join Eddie Davila for an in-depth discussion in this video Discrete vs. continuous, part of Statistics Foundations: Probability.
- For this chapter, there are three new terms … we'll need to understand. … Random variable, discrete, and continuous. … Let's begin with a random variable. … Why random? … Why do we use that word? … Well, as we perform experiments, we need to understand … that the value of the eventual outcome … of an experiment is unknown or random. … This is why we call the result … of an experiment a random variable. … The amount of rain that will fall in London this month … is a random variable. … The length of time you will wait in line … at Starbucks tomorrow, that, too, is a random variable. … As is the number of drinks … the 10th customer of the day orders. … These random variables can either be discrete … random variables or continuous random variables. … Let's begin with discrete random variables. … The number of drinks the next Starbucks customer … will order is very likely as low as zero. … Perhaps they just want a food item, … but probably no larger than 10. … And since they can't order half drinks, …
Eddie explains that probability is used to make decisions about future outcomes and to understand past outcomes. He covers permutations, combinations, and percentiles, and goes into how to describe and calculate them. Eddie introduces multiple event probabilities and discusses when to add and subtract probabilities. He describes probability trees, Bayes’ Theorem, binomials, and so much more. You can learn to understand your data, prove theories, and save valuable resources—all by understanding the numbers.