Sales data for two years are as follows. Data are aggregated with two months of sales (in 1,000 units) in each period.

	Period	Sales
Year 1	JanuaryFebruary	1332
	MarchApril	1637
	MayJune	1790
	JulyAugust	2030
	SeptemberOctober	1752
	NovemberDecember	1409
Year 2	JanuaryFebruary	1492
	MarchApril	1588
	MayJune	2151
	JulyAugust	2489
	SeptemberOctober	1938
	NovemberDecember	1578

Plot the data.

Fit a linear regression model to all the sales data.

In addition to the regression model, determine multiplicative seasonal index factors. A full cycle is assumed to be a full year.

Using the results from parts b) and c), prepare a forecast for the next year.