Let’s explain why the normal distribution is so important. (This is a section in the notes here.)| Applied Probability Notes
We consider distributions that have a continuous range of values. Discrete probability distributions where defined by a probability mass function. Analogously continuous probability distributions a…| Applied Probability Notes
There are some probability distributions that occur frequently. This is because they either have a particularly natural or simple construction. Or they arise as the limit of some simpler distributi…| Applied Probability Notes
Often we are interested in the magnitude of an outcome as well as its probability. E.g. in a gambling game amount you win or loss is as important as the probability each outcome. (This is a section…| Applied Probability Notes
(This is a section in the notes here.) Conditional probabilities are probabilities where we have assumed that another event has occurred.| Applied Probability Notes
(This is a section in the notes here.) Counting in Probability. If each outcome is equally likely, i.e. $latex \mathbb P( \omega ) = p$ for all $latex \omega \in \Omega$, then since (where $latex |…| Applied Probability Notes
(This is a section in the notes here.) We want to calculate probabilities for different events. Events are sets of outcomes, and we recall that there are various ways of combining sets. The current…| Applied Probability Notes
(This is a section in the notes here.) I throw a coin $latex 100$ times. I got $latex 52$ heads.| Applied Probability Notes
This is the appendix in the notes here.| Applied Probability Notes