Table of Contents
How do you find the expected value in X and Y?
– The expectation of the product of X and Y is the product of the individual expectations: E(XY ) = E(X)E(Y ). More generally, this product formula holds for any expectation of a function X times a function of Y . For example, E(X2Y 3) = E(X2)E(Y 3).
What is the covariance of X and Y?
The covariance between X and Y is defined as Cov(X,Y)=E[(X−EX)(Y−EY)]=E[XY]−(EX)(EY).
How do you solve for covariance?
- Covariance measures the total variation of two random variables from their expected values.
- Obtain the data.
- Calculate the mean (average) prices for each asset.
- For each security, find the difference between each value and mean price.
- Multiply the results obtained in the previous step.
What does it mean if covariance is zero?
The covariance is defined as the mean value of this product, calculated using each pair of data points xi and yi. If the covariance is zero, then the cases in which the product was positive were offset by those in which it was negative, and there is no linear relationship between the two random variables.
Can expected value be 0?
The expected value of any experiment can be zero but it does not mean that its real outcome will be zero. Let us look at an example: Consider a risky…
How do you prove that X and Y are independent?
X and Y are independent if and only if given any two densities for X and Y their product is the joint density for the pair (X,Y) i.e. Proof: • If X and Y are independent random variables and Z =g(X), W = h(Y) then Z, W are also independent.
Is E[xjy] a number or a function of Y?
Conditional expectations such as E[XjY = 2] or E[XjY = 5] are numbers. If we consider E[XjY = y], it is a number that depends on y. So it is a function of y. In this section we will study a new object E[XjY] that is a random variable.
How do you know if a pair of random variables are independent?
Random variables X and Y are independent if their joint distribution function factors into the product of their marginal distribution functions • Theorem. Suppose X and Y are jointly continuous random variables. X and Y are independent if and only if given any two densities for X and Y their product is the joint density for the pair (X,Y) i.e.
How do you compute E[xjy = y]?
We compute E[XjY = y]. The event Y = y means that there were y 1 rolls that were not a 6 and then the yth roll was a six. So given this event, X has a binomial distribution with n = y 1 trials and probability of success p = 1=5. So E[XjY = y] = np = 1 5 (y 1) Now consider the following process.