[Solved] DA5030 Problems 2

For this set of practice problems you should not use any forecasting packages. Instead write the codeyourself as demonstrated in the lessons. However, you may wish to compare your answers to those of yourpeers and to those from functions in packages.1. The built-in dataset USArrests contains statistics about violent crime rates in the US States.Determine which states are outliers in terms of murders. Outliers, for the sake of this question, aredened as values that are more than 1.5 standard deviations from the mean.2. For the same dataset as in (1), is there a correlation between urban population and murder, ,as one goes up, does the other statistic as well? Comment on the strength of the correlation. Calculatethe Pearson coecient of correlation in R.3. Based on the data on the growth of mobile phone use in Brazil (youll need to copy the dataand create a CSV that you can load into R or use the function from the gsheet package),forecast phone use for the next time period using a 2-year weighted moving average (with weights of5 for the most recent year, and 2 for other), exponential smoothing (alpha of 0.4), and linearregression trendline.4. Calculate the squared error for each model, , use the model to calculate a forecast for eachgiven time period and then the squared error. Finally, calculate the average (mean) squared error foreach model. Which model has the smallest mean squared error (MSE)?5. Calculate a weighted average forecast by averaging out the three forecasts calculated in (3)with the following weights: 4 for trend line, 2 for exponential smoothing, 1 for weighted movingaverage. Remember to divide by the sum of the weights in a weighted average