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

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Question: 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?

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

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