Join Eddie Davila for an in-depth discussion in this video Normal curve, part of Statistics Foundations: Probability.
- Discrete distributions tend to look like this. … We can use bar charts because each value is discrete. … All numbers are whole numbers. … But when you have continuous random variables, … there are an infinite number of possible outcomes. … Here are the wait times for 10 random travelers … on a single day at an airport. … No whole numbers and no repeated numbers. … And I'm guessing that if we had data for 50 more travelers, … it's very possible there still would not be … any repeated values. … In cases like this, we can say … that the possible outcomes are infinite. … Bar charts wouldn't work here, so instead we use curves … to illustrate the distribution of outcomes. … These curves are called probability densities. … The area under the curve represents … the probability of each and every outcome. … So for this probability density, … the probability of outcome A is X. … The probability of outcome B is Y. … Also since the area under the curve represents … every possible outcome, the entire area under the curve …
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.