Here's the question:



We have 10 values for some variable X, those being:



Observation # 1 2 3 4 5 6 7 8 9 10

X Value 5 8 10 4 5 12 2 6 3 6

U 1.38 .35 -1.51 -.49 .52 -2.73 2.83 -3.59 -4.71 -2.19



Also, I have been given 10 obs. on an independent random variable pulled from a normal distribution with mean=0 and variance=10. These represent the error terms in my model (u sub i). I am supposed to generate the values of the dependent variable Yi=1+.5Xi+ui.



Now, the question on the problem set (which I don't know if it has anything to do with error terms) says the since we know the true properties of the data, I can answer the following two questions (I'm noted that I don't need the Y's to answer the question):



a) What is the true variance of B^{hat}o



b) What is the true variance of B^{hat}1



Can anyone help? Im rather confused on what its meant by true properties. Thanks.