I want you to turn in a report for the simulation study we just did. The report should include the following three parts:

Your Matlab commands;
Graphical display from simulation (2): histograms plus normal curves for four different sample size m=5,25,50,100, with legend or title indicating the sample size for each figure.
Add some descriptions and conclusions about this simulation: Copy and paste the following, replacing all the (?) by a numerical value.
In this simulation, we first study the sampling distribution of sample mean of 5 observations (that is, m=5) from Weibull distribution with parameters a=2 and b=5. We use Matlab to generate a (?) by (?) matrix with each element is a random observation from the Weibull distribution. Then we calculate the mean cross row of the matrix and obtain a vector with length=(?) where each element of the vector is the sample mean of 5 observations. Finally, we use the Matlab function sdist to draw the histogram for the (?) sample means. We repeat this procedure for sample sizes m=25,50 and 100. We observe that the histograms all are mound-shaped and tend to cluster about the mean of Weibull(2,5), which is equal to (?). Furthermore, as the sample size m increases, there is less variation in the sampling distribution, that is, the histogram is more sharply centered at the mean.

By Central Limiting Theorem, we know that when the sample size m is large enough, the sampling distribution of the sample mean can be approximated by a normal distribution with mean equal to the population mean and variance is equal to the variance of the population distribution divided by m. To check this, we superpose a normal density curve on each figure with appropriate mean and variance. For example, when the sample size m=5, we plot the normal density curve with mean=(?) and variance =(?). The figures show that when the sample size m increases, the shape of the sampling distribution tends toward the shape of the normal distribution (symmetric and mound-shaped).