Discrete random variables: probability functions, expected value, variance and linear changes of scale and origin

What this note covers

1. From outcomes to a probability function
2. Estimating probabilities from data and recognising uniformity
3. Expected value as a weighted centre
4. Variance and standard deviation
5. Changing scale and origin
6. Using the distribution to compare practical outcomes
7. Connected reasoning across General discrete random variables
8. Error analysis and final checks for General discrete random variables

8 sections · 10 key terms & formulas · 6 common mistakes