请问下面这道题的解法为什么和本题的不一样？

问题如下：

c. Using the results from part a and part b, and the correlation between the two explanatory variables, estimate the parameters for the full model:

$Y=\alpha+\beta_1X_1+\beta_2X_2$

选项：

解释：

The key statement from the chapter is “the estimator $\widehat\beta_1$ converges to $\beta_1 + \beta_2\delta$”

So, part a gives that:

$\beta_1 + \beta_2\delta_1 = 0$

And part b gives that:

$\beta_2 + \beta_1\delta_2 = -1.479$

$\delta_1=\frac{Cov[X_1,X_2]}{V[X_1]}=0.467/0.933=0.501$

and

$\delta_2=0.467/0.934=0.5$

Note: In this case these quantities are essentially equal, but that will not usually be the case.

Plugging back in the 2 * 2 system of equations:

$\beta_1 + 0.501\beta_2 = 0$

$\beta_2 + 0.5\beta_1 = -1.479$

Solving yields that

$\beta_1=0.989, \beta_2=-1.9733$

And plugging these back into the equation to find alpha:

$\overline Y=\alpha+\beta_1\overline X_1+\beta_2\overline X_2=-2$

$Y=-2+0.989X_1-1.9733X_2$