Question

3.       Here are quarterly data for the past two years. From these data, prepare a forecast for the upcoming year using linear regression.
	Period	Actual
	1.00	300.00
	2.00	540.00
	3.00	885.00
	4.00	580.00
	5.00	416.00
	6.00	760.00
	7.00	1191.00
	8.00	760.00
	What are the forecasts for periods 9, 10, 11, and 12?

Answer 1

By running regression of the form Y = a+bX

Where Y is actual and X is period, we get results of the form,

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.61
R Square	0.37
Adjusted R Square	0.27
Standard Error	241.49
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	1	2,09,738.67	2,09,738.67	3.60	0.11
Residual	6	3,49,895.33	58,315.89
Total	7	5,59,634.00
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	361.00	188.17	1.92	0.10	-99.42	821.42
Period	70.67	37.26	1.90	0.11	-20.51	161.84

Period	Actual
1	300
2	540
3	885
4	580
5	416
6	760
7	1191
8	760
9	997
10	1068
11	1138

Forecasts,

Period 9 = 361+70.67*9 = 997.03

Period 10 = 361+70.67*10 = 1067.7

Period 11 = 361+70.67*11 = 1138..37