Question

uppose the Kalamazoo Brewing Company (KBC) currently sells its microbrews in Illinoise. The company’s marketing department has collected data from its distributors in each state. This data consists of the quantity and price (per case) of microbrews sold in each state, as well as the average income (in thousands of dollars) of consumers living in various regions of each state.

Assuming that the underlying demand relation is a linear function of price and income, use the data provided to obtain least squares estimates of Illinois’s demand for KBC microbrews.

Instruction: If the estimate is negative, enter a negative number (-) in the equation. Enter your responses rounded to two decimal places.

Quantity	Price	Income
575	31.26	33.95
674	30.69	35.51
616	31.54	28.78
183	27.41	30.44
501	29.75	31.28
578	29.48	33.77
590	28.94	38.31
445	28.17	34.01
603	28.58	32.53
713	28.57	31.69
337	30.06	32.26
230	29.36	31.57
403	28.81	32.75
383	32.52	29.48
568	32.02	35.91
698	32.91	34.85
826	28.45	34.06
789	26.85	38.92
645	30.49	35.94
601	31.72	38.05
467	31.23	36.48
429	31.28	37.61
552	28.89	38.29
553	31.13	36.9
562	27.52	39.22
352	30.02	34.21
611	31.38	33.97
346	29.08	38.53
354	28.8	34.4
401	27.64	34.01
253	30.47	34.24
524	30.97	38.29
211	32.85	34.66
666	30.11	41.38
468	29.48	32.14
585	28.41	29.16
578	29.96	35.05
656	30.46	37.11
571	32.86	32.94
454	28.49	32.7
510	30.67	33.14
672	31.92	33.73
499	28.44	41.92
560	27.94	35.06
848	29.74	32.71
617	29.54	37.96
530	31.34	37.38
649	30.08	35.55
824	29.13	42.89
626	31.72	37.17

Q = __+__ Price__ +__ Income

Answer 1

Excess regression summary output as follows.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.29
R Square	0.09
Adjusted R Square	0.05
Standard Error	151.15
Observations	50
ANOVA
	df	SS	MS	F	Significance F
Regression	2	100540.9347	50270.47	2.200256	0.12205759
Residual	47	1073835.145	22847.56
Total	49	1174376.08
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-42.65	496.56	-0.09	0.93	-1041.60	956.29
Price	2.62	13.99	0.19	0.85	-25.53	30.76
Income	14.32	6.83	2.10	0.04	0.58	28.05

Estimated regression equation:

Q = -42.65 + 2.62 x Price + 14.32 x Income