To be able to receive full credit, you must show your computations in the space provided for each question.

Date	Percent
2013-01-01	5.60
2013-04-01	5.30
2013-07-01	5.40
2013-10-01	7.00
2014-01-01	6.20
2014-04-01	5.80
2014-07-01	6.00
2014-10-01	7.70
2015-01-01	6.90
2015-04-01	6.50
2015-07-01	6.70
2015-10-01	8.60
2016-01-01	7.60
2016-04-01	7.40
2016-07-01	7.60
2016-10-01	9.40
2017-01-01	8.44
2017-04-01	8.24
2017-07-01	8.43
2017-10-01	10.44
2018-01-01	9.34

1). Regress the de-seasonality component of quarterly e-commerce retail sales on time component. In the space provided below, show your regression output and the regression equation using trend-and-season predictive model from the simple linear regression output.

2). Compute a forecast for the series of third quarter on the time plot of quarterly e-commerce retail sales. Note that the series end on the first quarter with t=21. Make sure to include the seasonality ratio for the appropriate quarter corresponding to the value of t.