Q3. a. If a random variable X has mean 3 and standard deviation 5, then find out the variance of a variable
Y=2X-5.
b. If each observation in the set of values (X, Y) is divided by 100, then find the correlation coefficient of
new data set?
a. We use the linearity of a mean of random variables and receive: "E[Y]=E[2X-5]=2E[X]-E[5]=2E[X]-5=6-5=1".
We remind that the standard deviation squared is: "\\sigma_Y^2=E[(Y-E[Y])^2]=E[Y^2-2YE[Y]+(E[Y])^2]=E[Y^2]-2(E[Y])^2+(E[Y])^2=E[Y^2]-(E[Y])^2=E[4X^2-20X+25]-1=4E[X^2]-20E[X]+24=4E[X^2]+24-20\\cdot3=4E[X^2]+24-60=4E[X^2]-36"
We find "E[X^2]" from equality: "25=\\sigma_X^2=E[X^2]-(E[X])^2=E[X^2]-9". We receive: "E[X^2]=34". Finally, we get: "\\sigma_Y^2=4\\cdot34-36=100" and "\\sigma_Y=10".
Thus, the mean is 1 and the standard deviation is 10.
b. We remind that the formula for Pearson's correlation coefficient(when applied to sample) is:
"r_{xy}=\\frac{\\sum_{i=0}^n(x_i-\\bar{x})(y_i-\\bar{y})}{\\sqrt{\\sum_{i=0}^n(x_i-\\bar{x})^2}\\sqrt{\\sum_{i=0}^n(y_i-\\bar{y})^2}}". As we can see from the formula, the coefficient will remain unchanged.
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