Question

The accompanying data shows the demand for one type of chip used in industrial equipment from a small manufacturer.

a. Construct a chart of the data. What appears to happen when a new chip is​ introduced?

b. Develop a causal regression model to forecast demand that includes both time and the introduction of a new chip as explanatory variables.

c. What would the forecast be for the next month if a new chip is​ introduced? What would it be if a new chip is not​ introduced?

Month New Chip Introduced ooooooo Demand 3949 3544 6138 7752 10700 7766 5482 8789

Answer 1

ANSWER:

a. chart of the data construction. What appears to happen when a new chip is​ introduced is

Regression Statistics
Multiple R	0.944266829
R Square	0.891639844
Adjusted R Square	0.881319829
Standard Error	1513.459395
Observations	24
ANOVA
	df	SS	MS	F	Significance F
Regression	2	395804463.8	197902231.9	86.39908539	7.34735E-11
Residual	21	48101746.12	2290559.339
Total	23	443906210
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	3097.183006	658.7938872	4.701292872	0.000121691	1727.146117	4467.219894
Month	535.5705134	44.68196631	11.98627898	7.43688E-11	442.6492776	628.4917491
Chip introduced	4955.863462	829.9306893	5.971418488	6.30595E-06	3229.92811	6681.798814

b. Develop a causal regression model to forecast demand that includes both time and the introduction of a new chip as explanatory variables.
so,

Demand= 3097 + 535.5*month + 4955.8*Chip introduced

c. The forecast be for the next month if a new chip is​ introduced, it would be if a new chip is not​introduced is

Forecast if new chip is introduced for month 25

= 3097 + 535.5*25 + 4955.8*1

= 21442

Forecast if new chip is not introduced for month 25

= 3097 + 535.5*25 + 4955.8*0

=16486