The correlation between X and Y
A) cannot be negative since variances are always positive.
B) is the covariance squared.
C) can be calculated by dividing the covariance between X and Y by the product of the two
standard deviations.
D) is given by corr(X,Y) = COV(X,Y)/[VAR(X)*Var(Y)]
Answer: C
Probability
- The sample average is a random variable and
- If variables with a multivariate normal distribution have covariances that equal zero, then
- Assume that Y is normally distributed N(miu, sigma) . Moving from the mean (miu) 1.96 standard deviations to the left and 1.96 standard deviations to the right, then the area under the normal p.d.f. is
- To standardize a variable you
- For a normal distribution, the skewness and kurtosis measures are as follows:
- The expected value of a discrete random variable
- The cumulative probability distribution shows the probability
- The probability of an event A or B (Pr(A or B)) to occur equals
- The probability of an outcome