Problem 3 (32 marks) The London Metropolitan (Met) Police has been informed of your expertise in Analytics and has commissioned you to undertake an anal , sis of reported offences between April 2010 and March 2019 (nine financial year), with view to develop forecasts for the following yea. (Apr 2013 - Mar 2020). For that pirpose, they have recorded in a separate worksheet offence data for that year. Given the lin ited time available they would like you to focus on four crime categories burglary, sexual Offences, Theft, and Violence Against the . erson (11 subcategories it is recommended that you search for more information awOut the n caring of these categorIt5). You will find me data in the _xcel le "Met Police offence Data 2010-2020 -wal-x Make sure to a wa sjustify you. answers. -) Plot the data (Apr 2010 - Mar 2019) as time series (11 of them) Using the graphs, summarise which series exhibit trends (linear / non-linear) and/ or seasonality. b Analyse for seasonality the data for "Burglary - Business and Community", "Burglary - Residential", "Rape", "Bicycle Theft", "Violence with Injury", "Violence without Injury" include the seasonal indices for each month, and comment on the high seasonal and low seasonal sales months. Do the seasonal indices make intuitive sense. Discuss. c; For each of the three offence types exhibiting highest seasonality in b), use two appropriate forecasting techniques to forecast offences for Apr 2019 to Mar 2020. For each of the three time-series, compare the results obtained with the two methods using the mean error (bias), the mean absolute deviation (MAD), the mean square error (MSE), and the mean absolute percentage error (MAPE) of the forecasts on the data between Apr 2010 and Mar 2019. d) Check and discuss autocorrelation and error randomness for each series. e) Produce forecasts for the three offences in c) for Apr 2019 to Mar 2020 using your two chosen methods and compare your results with actual values for Apr 2019 - Mar 2020 using again the mean absolute deviation (MAD), the mean souare error (MSE), and the mean absolute percentage error (MAI E) for that period. Are the best performing forecasting methods still the same as in c).' f) Discuss correlations between the 11 offence subcategories, potential issues with calculating these, and how to alleviate them