AI engineering glossary · Probability
What is linearity of expectation?
Linearity of expectation: The expected value of a sum of random variables equals the sum of their expected values, and E[aX + b] = a E[X] + b. It holds whether or not the variables are independent, which makes many calculations easy.
Linearity of expectation: an example
If a delivery costs Rs 40 on average and a return costs Rs 25 on average, the expected total is Rs 65 regardless of any link between them.
Related terms
More Probability terms
- Marginal distribution
- Marginal probability
- Markov chain
- Markov chain Monte Carlo
- Markov property
- Markov's inequality
- Maximum likelihood estimation
- Median
Where you learn it
Linearity of expectation is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.