formal response from Peg Jones's to Stephen Ruth explaining the numbers numbers and calculations. Which costs are correlated with the average age of the aircraft? What is the slope and beta? Explain the coefficient of determination and covariance. Explain how this information benefits each airline. Finally, Stephen wants to know: a. If Northern's average age gets to 20,000 hours how much will the Airframe and Engine cost. b. If Southeast's average age gets to 12,000 hours how much will the Airframe and Engine cost?

Southwest Data: Engine

SUMMARY OUTPUT				Observation	Predicted Average Age (Hours)	Residuals
					1	6249.205	-1142.2
Regression Statistics				2	7597.86	547.1399
Multiple R	0.664207				3	8622.33	-1262.33
R Square	0.441171				4	6507.63	-734.63
Adjusted R Square	0.329406				5	6229.592	920.4078
Standard Error	1208.183				6	7716.689	1647.311
Observations	7				7	8234.693	24.30695
ANOVA
	df	SS	MS	F	Significance F
Regression	1	5761873	5761873	3.947285	0.103676
Residual	5	7298527	1459705
Total	6	13060399
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	3957.991	1747.033	2.26555	0.072844	-532.9	8448.881	-532.9	8448.881
Engine Cost	115.3683	58.06804	1.986778	0.103676	-33.9004	264.6369	-33.9004	264.6369

Southwest Airframe Data					Observation	Predicted Average Age (Hours)	Residuals
					1	5562.136	-455.136
					2	6929.908	1215.092
SUMMARY OUTPUT				3	7815.308	-455.308
					4	7764.93	-1991.93
Regression Statistics				5	6953.838	196.1621
Multiple R	0.618293				6	7890.876	1473.124
R Square	0.382287				7	8241.005	17.99482
Adjusted R Square	0.258744
Standard Error	1270.243
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	1	4992815	4992815	3.094368	0.138888
Residual	5	8067584	1613517
Total	6	13060399
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	3762.368	2072.164	1.815672	0.129126	-1564.3	9089.035	-1564.3	9089.035
Airframe Cost	125.9459	71.59754	1.759082	0.138888	-58.1014	309.9933	-58.1014	309.9933

Northwest Engine Data:

SUMMARY OUTPUT		RESIDUAL OUTPUT
Regression Statistics		Observation	Predicted Average Age	Residuals
Multiple R	0.854976		1	8136.635	-1624.63
R Square	0.730984		2	9269.395	-865.395
Adjusted R Square	0.677181		3	12140.24	-1063.24
Standard Error	2281.261		4	13751.47	-2034.47
Observations	7		5	10802.74	2472.262
			6	11868.73	3346.266
ANOVA			7	18620.78	-230.784
	df	SS	MS	F	Significance F
Regression	1	70704849	70704849	13.58624	0.014205
Residual	5	26020751	5204150
Total	6	96725599
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	683.564	3210.953	0.212885	0.839824	-7570.45	8937.582	-7570.45	8937.582
Engine Cost	222.5462	60.37684	3.685952	0.014205	67.34254	377.7498	67.34254	377.7498

Northwest Airframe data:

SUMMARY OUTPUT				RESIDUAL OUTPUT
Regression Statistics				Observation	Predicted Average Age	Residuals
Multiple R	0.798457				1	9836.991	-3324.99
R Square	0.637533				2	7668.494	735.5065
Adjusted R Square	0.56504				3	12326.98	-1249.98
Standard Error	2648.01				4	12074.83	-357.83
Observations	7				5	10442.15	2832.847
					6	17064.27	-1849.27
ANOVA					7	15176.29	3213.714
	df	SS	MS	F	Significance F
Regression	1	61665807	61665807	8.794377	0.031318
Residual	5	35059793	7011959
Total	6	96725599
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-9641.66	7394.206	-1.30395	0.249052	-28649.1	9365.749	-28649.1	9365.749
Airframe Cost	315.1886	106.284	2.965531	0.031318	41.97683	588.4004	41.97683	588.4004