A forecaster used the regression equationQt = a + bt + c1D1 + c2D2 + c3D3and quarterly sales data for 2004I–2021IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and D1, D2 andD3 are dummy variables for quarters I, II, and III. DEPENDENT VARIABLE:QTR-SQUAREF-RATIOP-VALUE ON FOBSERVATIONS:640.8768107.9820.0001VARIABLE PARAMETER ESTIMATESTANDARD ERRORT-RATIOP-VALUEINTERCEPT 30.012.802.340.0224T 1.50.702.140.0362D1 10.03.003.330.0015D2 25.07.203.470.0010D3 40.015.802.530.0140 Using the estimation results given above, the predicted level of sales in 2022II is _______ units.

Answered: A forecaster used the regression…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A forecaster used the regression equation

Q_t = a + bt + c₁D₁ + c₂D₂ + c₃D₃

and quarterly sales data for 2004I–2021IV (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and D₁, D₂ andD₃ are dummy variables for quarters I, II, and III.

DEPENDENT VARIABLE:	QT	R-SQUARE	F-RATIO	P-VALUE ON F
OBSERVATIONS:	64	0.8768	107.982	0.0001
VARIABLE		PARAMETER ESTIMATE	STANDARD ERROR	T-RATIO	P-VALUE
INTERCEPT		30.0	12.80	2.34	0.0224
T		1.5	0.70	2.14	0.0362
D1		10.0	3.00	3.33	0.0015
D2		25.0	7.20	3.47	0.0010
D3		40.0	15.80	2.53	0.0140