# Simple Linear Regression

$$\begin{array}{c|c|c|c|c|c|c|c|c|c|c|} \text{Obs}\# & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10\\\hline X & 5 & 8 & 10 & 4 & 5 & 12 & 2 & 6 & 3 & 6 \end{array}$$

These values are given and then we are provided with error terms, one for each observation, pulled from a normal distribution with mean=0 and variance=10 and we are supposed to generate the values of our dependent variable Y using the formula $Y_{i}=1+.5X_{i}+u_{i}$

The first question is asking: since we know the true properties of the data, then what is the true variance of $\hat{\beta_{o}}$ and $\hat{\beta_{1}}$. But I'm not really sure what that is asking: what is meant by true properties? Nothing was ever really explained or mentioned anything about true properties so I'm rather confused. Would anyone mind clarifying please?

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What is $\beta_0$ and $\beta_1$? –  utdiscant Feb 8 '13 at 7:56
They are B0=1 and B1=.5 –  USC Feb 8 '13 at 8:09