- #1
squenshl
- 479
- 4
Homework Statement
Suppose we have a discrete random variable whose values $X = x$ can include the value $0$. Some examples are: ##X\sim \text{Binomial}(n,p)## with ##x = 0,1,2,\ldots,n## and ##X\sim \text{Poisson}(\lambda)## with ##x = 0,1,2,3,\ldots## Sometimes we can only observe these variables when ##X = x \neq 0##, i.e. when ##x## is not zero. These distributions are known as the non-zero (adjustments) to the original distributions. For the examples discussed above, they are the Non-Zero Binomial and Non-Zero Poisson respectively. Show that the variable ##Y = x## for ##x \neq 0## has:
1. Probability function ##\text{Pr}(Y=y)=c\text{Pr}(X = x)## for ##x \neq 0## and that ##c = \frac{1}{1-\text{Pr}(X=0)}##.
2. ##E(Y) = cE(X)##.
3. ##\text{Var}(Y) = c\text{Var}(X)+c(1-c)\left((E(X)\right)^2##.
4. With respect to the two non-zero examples above, discuss when this adjustment can be ignored, i.e. it has little impact on the what is actually observed.
Homework Equations
##E(Y) = \sum_{i=1}^{n} y_i \text{Pr}(Y=y)##.
##\text{Var}(Y) = E(Y^2)-E(Y)^2##.
The Attempt at a Solution
I'm not actually sure what they are trying to for 1. 2. and 3. Do we have to apply the actual density functions of the 2 respective distributions above or what?