The local department store suffered heavy damage when a storm struck. The store had to close for four months (September through December). The store is now in a dispute with its insurance carrier about the dollar value of lost sales during the closure.

There are two key issues:

1. The amount of sales that would have occurred if the storm had not happened.
2. The amount of compensation adjustment that needs to be made due to excess sales due to increased business activity after the storm. In other words, did people rush to buy more goods the four months after the storm took place?

Sales for Our Department Store ($ millions)

Month	Year 1	Year 2	Year 3	Year 4	Year 6
January		1.45	2.31	2.31	2.56
February		1.80	1.89	1.99	2.28
March		2.03	2.02	2.42	2.69
April		1.99	2.23	2.45	2.48
May		2.32	2.39	2.57	2.73
June		2.20	2.14	2.42	2.37
July		2.13	2.27	2.40	2.31
August		2.43	2.21	2.50	2.23
September	1.71	1.90	1.89	2.09
October	1.90	2.13	2.29	2.54
November	2.74	2.56	2.83	2.97
December	4.20	4.16	4.04	4.35

Sales for All County Department Store ($ Millions)

Month	Year 1	Year 2	Year 3	Year 4	Year 6
January		46.80	46.80	43.80	48.00
February		48.00	48.60	45.60	51.60
March		60.00	59.40	57.70	57.60
April		57.60	58.20	53.40	58.20
May		61.80	60.60	56.40	60.00
June		58.20	55.20	52.80	57.00
July		56.40	51.00	54.00	57.60
August		63.00	55.80	60.60	61.80
September	55.80	57.60	49.80	47.40	69.00
October	56.40	53.40	54.60	54.60	75.00
November	71.40	71.40	65.40	67.80	85.20
December	117.60	114.00	102.00	100.20	121.80

Questions:

You do not have to actually perform the calculations. What analyses would use perform to answer the following:

1. An estimate of sales lost for our department store had there been no storm.
2. An estimate of countywide department store sales had there been no storm.
3. Based on results from (1) and (2) above, a case for or against excess storm-related sales.