IAI Actuarial Core Principles · Actuarial Statistics · Expectations and conditional expectations
A non-negative integer-valued random variable N has P(N > n) = 0.6^n for n = 0, 1, 2, .... What is E[N]?
Using E[N] = Σ P(N > n) for n ≥ 0, the sum is the geometric series Σ0.6^n = 1/0.4 = 2.5. This matches a geometric distribution on 1,2,3,... with success probability 0.4.
- A1.50Correct
- B0.60
- C2.50
- D1.00
- 1.67
Explanation
For non-negative integer variables, E[N] = sum over n≥0 of P(N > n) = sum of 0.6^n = 1/(1-0.6) = 2.5. Checking: P(N=0) = 1 - 0.6 = 0.4, so N is geometric on 1,2,... with p=0.4, giving mean 1/0.4 = 2.5. Hence the key is 2.5 and not 1.5.
Did you get it right without looking?
One question tells you little. A timed set on Expectations and conditional expectations shows your real accuracy, how long you take and where you lose marks.
More Expectations and conditional expectations questions
- X and Y are random variables with E[Y | X] = 3X + 2. Given E[X] = 4, what is E[Y]?
- X and Y satisfy E[Y|X] = 2 + 3X. X has mean 4 and variance 5. Var(Y|X) = 10 for all X. What is Var(Y)?
- Given Λ = λ, the claim count N is Poisson(λ). Λ has an exponential distribution with mean 2. What is Var(N)?
- The number of claims N on a policy in a year has a Poisson distribution with mean Λ, where Λ is uniformly distributed on (0, 4). What is Var…
- X is uniform on (0, 6). What is E[X²]?
- The number of claims N in a year has mean 4. Given N, each claim amount is independent with mean Rs 5,000. Using the law of total expectatio…