Better Understanding Continuous Distributions and Stochastic Modeling via the Normal Distribution

Overview

In this topic we’re going to go deeper into the concepts of continuous probability distributions (PDFs) and stochastic modeling. And we’re going to do this by getting to know the normal distribution quite closely. We’ll look at and formally define the normal probability distribution function itself, while building some intuition around it. We’ll begin to talk about why that matters, practically speaking. And we’ll build some skills at getting probabilities as areas under the normal curve, and getting z-score values for for given probabilities. In doing so, you’ll be getting pretty good at using a standard normal table and Excel for these tasks too.

My notes

Here are my lecture notes – the ones I wrote up when I lectured on this topic. They’re not perfect, but if you’re in my class then they should be helpful when you go to create your own “perfect” set of lecture notes.

When you’re ready, proceed by working your way through the self-assessments (under “Lesson Assessments”) below.

Once you’ve clicked through those, use the green button to move on to the next lesson (or to finish up if there are no other lessons).


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The following schedules are for Alex’s in-class students: