Random variables
Random variables with zero correlation are not necessarily independent. Give a simple example.
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Let X be a normally-distributed random variable with
Mean zero. Let Y = X^2. Obviously, X and Y are not independent: knowing X, gives the value of Y.
The covariance of X and Y is Cov(X,Y) = E(XY) - E(X)E(Y) = E(X^3) - 0*E(Y) = E(X^3) = 0,
because the distribution of X is symmetric around zero. correlation r(X,Y) = Cov(X,Y)/Sqrt[Var(X)Var(Y)] = 0, the random variables are not independent, but correlation is zero.
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Define the term Correlation and describe Correlation formula in brief.
Instructions: Do your work on this question and answer sheet. Please print or write legibly, and, as always, be complete but succinct. Record your answer and your supporting work in the designated space. Explain your method of solution and be sure to label clearly any
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Name and elaborate the four components of time series in brief.
Explain sampling bias and describe how random sampling serves to avoid bias in the process of data collection.
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The table below illustrates the relationship between two variable X and Y. A
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