Hi guys,

May I obtain some feedback on my attempts on this question:

The question is as follows:


1) The first part required me to find an estimate for theta using MLE where I first defined the log likelihood function as:


I then differentiated this with respect to theta and equated it to 0 to solve for an estimator of theta where I obtain:
\hat{\theta} = \frac{\sum y}{n\alpha}

2) The second part requires that I estimate the variance of the MLE I have just derived so I took the following approach:
var[\hat{\theta}] = var\left[ \frac{\sum y}{n\alpha}    \right]
I worked on the RHS using variance properties var[Y] = b^2 var[X] to obtain
\left(  \frac{1}{n\alpha}  \right)^2 var[\sum y]
The question originally gave var[y] = \alpha \theta^2 so substituting this in gives:
\frac{\theta^2}{n \alpha}
Finally I substitute the estimate for theta I derived in part 1) to obtain an answer of:
\frac{(\sum y)^2}{n^3 \alpha^3}

Thank you in advance for any feedback given
Lin