Probability Distributions
Functions describing the probability of different outcomes of random events.
Just because something is random does not mean every outcome is equally likely. Probability distributions describe how likely each possible outcome of a random event is.
To get started, familiarize yourself with these three probability distributions:
- The normal distribution (continuous processes with a central tendency)
- The Poisson distribution (counts)
- The binomial distribution (ratios, proportions, binary data)
The video below introduces these and provides some intuition.
There are many other useful probability distributions which we will learn about as we progress, but these three form the starting point for many analyses.
The last chapter in this section introduces hypothesis testing.
What level of detail do I need for the exam?
If you are using this book in the context of one of my courses, please note the following:
- You do not need to master every detail in this section. The goal is a working understanding you can build on.
- Aim to finish this section within a day. We will revisit the concepts extensively in the following sections.
- On the exam, probability distributions only come up in the context of regression analysis, so focus your efforts on those sections.