The following is a partial printout from a Regression routine run on quarterly seasonal data with a trend in order to obtain a regression forecasting model. There were 20 consecutive quarters in the original time series. Time period 1 corresponds to a 1st quarter value. The trend variable is t, and the 3 dummy variables representing Quarters 1, 2 and 3 are Qtr1, Qtr2, and Qtr3 resp. Use the printout below to forecast the value of the time series for time period 23. Round your forecast to 1 decimal place.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.988
R Square	0.976
Adjusted R Square	0.968
Standard Error	0.217
Observations	20
ANOVA
	df	SS	MS	F	Significance F
Regression	4	21.248	5.312	156.235	0.000
Residual	15	0.516	0.034
Total	19	21.282
Variables	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	5.7	0.162	37.347	0.000	5.711	6.426
t	0.6	0.012	12.023	0.000	0.119	0.172
Qtr1	-0.6	0.157	-8.657	0.000	-1.710	-1.017
Qtr2	-2.9	0.155	-13.112	0.000	-2.375	-1.692
Qtr3	0.3	0.154	-1.981	0.073	-0.643	0.034