Reference no: EM133083395

Use the data on after-tax income reported in the Excel file . 

1. Use GRETL to draw a histogram (or frequency distribution) of the data, choosing 15 bins, and comment on the results.
2. Use GRETL to construct a kernel density estimate of the distribution of Income and comment on the distribution? As mentioned in class estimating a density entails choosing a kernel function (choose the normal distribution or Gaussian kernel) and bandwidth (choose automatic selection of bandwidth). Theoretically, the bandwidth determines how smooth the estimated density graph will look. The choice of the kernel function does nor matter i.e. we could choose the Gaussian kernel or another kernel function. For example, GRETL also gives you the option to choose the Epanechnikov kernel.
3. Do the results in (a) and (b) give rise to the same conclusions about the distribution of income?
4. Use GRETL to draw Boxplot of the data and comment on the presence of outliers.
5. Use GRETL to construct a normal Quantile-Quantile (QQ) plot. In doing so, use the sample mean and sample variance for normal quantiles). Based on your inspection of the QQ plot does it look as if the income can be represented by a normal distribution? Briefly explain.