: (Y1 ) is the Company-Z daily sales along the period Pre-COVID-19 (November and December 2019); (Y2) is the same Company-Z daily sales but during the period Post-COVID-19 (April and May 2020); (X1 ) is the daily inventory holding cost during the period Pre-COVID-19 (November and December 2019); while (X2 ) is the same daily inventory holding cost but during the period Post-COVID-19 (April and May 2020). Accordingly, in your analysis, you will depend on two main random variables over two time series. The first random variable is the Company-Z daily sales, and the second random variable is the Company-Z daily inventory holding cost. Therefore, the two random variables will be chosen over two periods of time: the first is (Pre-COVID-19: November and December 2019), and the second is (Post-COVID-19: April and May 2020). Your task is to prepare comprehensive report to the company, fulfilling specific requirements outlined below in point..

QUESTION(2) Calculate the average daily inventory holding cost during Pre- and Post- COVID19 (X1 AND X2)? Explain whether this average is considered as population parameters or sample statistics? Justify your answer?[15 marks]

\f24/Nov/2019 25/Nov/2019 26/Nov/2019 27/Nov/2019 28/Nov/2019 |29/Nov/2019 3225.8 3225.7 3227.3 3226.2 3225.6 3226.8 8.1 7.9 8.2 7.8 8.4 7.9 24/Apr/2020 25/Apr/2020 26/Apr/2020 27/Apr/2020 28/Apr/2020 29/Apr/2020 1714.5 1714.4 1715.4 1717.9 1716.2 1716.5 10.5 12.0 12.7 10.2 12.3 11.6 30/Nov/2019 1/Dec/2019 2/Dec/2019 3/Dec/2019 4/Dec/2019 5/Dec/2019 3224.4 3228.5 3227.0 3224.5 3225.0 3227.7 8.1 7.7 7.9 8.0 8.0 7.9 30/Apr/2020 1/May/2020 2/May/2020 |3/May/2020 4/May/2020 5/May/2020 1711.6 1717.5 1721.6 1713.2 1713.9 1709.1 15.3 11.8 6.4 12.4 12.8 14.4 6/Dec/2019 3228.6 7/Dec/2019 8/Dec/2019 9/Dec/2019 3228.4 10/Dec/2019 11/Dec/2019 3227.0 7.8 3227.0 7.5 3227.6 7.9 3226.8 8.1 6/May/2020 7.6 7.6 7/May/2020 8/May/2020 |9/May/2020 1721.2 1720.1 10/May/2020 1713.9 11/May/2020 1712.7 9.5 1722.3 9.6 1719.7 9.5 12.0 8.6 11.1 12/Dec/2019 13/Dec/2019 14/Dec/2019 15/Dec/2019 16/Dec/2019 17/Dec/2019 3229.0 3224.0 3223.6 3228.0 3226.1 3226.5 7.7 7.9 8.0 7.6 8.1 8.0 12/May/2020 13/May/2020 14/May/2020 15/May/2020 16/May/2020 17/May/2020 1713.9 1711.8 1719.0 1720.8 1715.8 1717.4 14.4 12.8 8.0 9.9 13.7 8.118/Dec/2019 19/Dec/2019 20/Dec/2019 21/Dec/2019 22/Dec/2019 23/Dec/2019 3229.2 3223.5 3227.3 3225.5 3229.1 3225.6 7.6 8.7 7.8 7.8 7.7 8.3 18/May/2020 19/May/2020 20/May/2020 21/May/2020 22/May/2020 23/May/2020 1716.0 1710.9 1716.7 1716.4 1715.6 1716.6 11.0 14.8 10.2 11.0 11.2 12.6 24/Dec/2019 25/Dec/2019 26/Dec/2019 27/Dec/2019 28/Dec/2019 29/Dec/2019 3224.2 3226.5 3225.4 3224.1 3227.8 3226.7 8.2 8.1 8.1 8.4 7.6 7.9 24/May/2020 25/May/2020 26/May/2020 |27/May/2020 28/May/2020 29/May/2020 1714.6 1719.1 1716.0 1713.4 1719.2 1718.5 11.7 10.5 10.1 12.9 10.7 8.0 30/Dec/2019 31/Dec/2019 3228.5 3225.4 7.6 7.8 30/May/2020 31/May/2020 1717.4 1720.9 10.2 10.1