Simulate 100 random numbers from a Normal distribution with mean 5 and variance 4. Use set.seed so that the same samples are obtained each time you run the code. Store the samples with variable name X. Use quantile-quantile plot to see if the distrbution of the sample is close to a normal distribution. Interpret the plot. You can use the default qqnorm and qqplot function or the qqPlot function from the "qualitytool" package in R. (4 points) Make a transformation Y=exp(X). Now Y can be considered as a random sample of size 100 from a log Normal distribution with u = 5 and w = 2. Plot a histogram on Y. Comment on the shape of the distribution of Y (3) Use qqPlot function with the distrbution name "lognormal" to contruct a quantile quantile plot on Y. Interpret the plot. Don't forget to install and load the packages "qualityTools" and MASS". (3 points)