In my previous two posts I sketched the frame of the big picture around probability distributions. In my introductory post I gave some intuition about the general concept and talked about the two major kinds: discrete and continuous distributions. … [Continue reading]
In my previous post I introduced you to probability distributions. In short, a probability distribution is simply taking the whole probability mass of a random variable and distributing it across its possible outcomes. Since every random variable … [Continue reading]
If you want to take your understanding of probabilities to the next level, it's crucial to be familiar with the concept of a probability distribution. In short, a probability distribution is an assignment of probabilities or probability … [Continue reading]
A few posts ago I introduced you to the "three M's" of statistics — the concepts of mean, mode, and median. Today I want to talk to you about a related concept called variance. While the three M's measure the central tendency of a collection of … [Continue reading]
Expected value is another central concept in probability theory. It is a measure of the "long-term average" of a random variable (random process). I know this doesn't sound too clear, but in this post I'm going to explain exactly what it … [Continue reading]
The law of large numbers is one of the most important theorems in probability theory. It states that, as a probabilistic process is repeated a large number of times, the relative frequencies of its possible outcomes will get closer and closer … [Continue reading]
