Complete the problems below from the textbook. You will need to use the "Baseball 2016 Data,"...

Question

Complete the problems below from the textbook. You will need to use the "Baseball 2016 Data," "Lincolnville School District Bus Data," and the "Century National Bank Data" files for this assignment.These files have been attached.

Chapter 13 – Problem 63
Chapter 13 – Problem 64
Chapter 14 – Problem 35
Chapter 14 Case A – Century National Bank

For problems requiring computations, please ensure that your Excel file includes the associated cell computations and/or statistics output. This information is needed in order to receive full credit on these problems.

Submit output in one Excel file. I have uploaded an excel file labeled Week 7 Stats the math problems are on each tab.

week-7-stats-ivb5o1gx.xlsx sym-506-rs-century-national-bank-data-4-dyljvbl3.xls sym-506-rs-lincolnville-school-district-bus-data-13-iakkktdz.xls sym-506-rs-baseball-2016-data-5-ty1rov02.xlsx

Mohd · Accepted Answer

Sheet2
	SUMMARY OUTPUT
	Regression Statistics
	Multiple R	0.71
	R Square	0.50
	Adjusted R Square	0.48
	Standard Error	427738.11
	Observations	30.00
	ANOVA
		df	SS	MS	F	Significance F
	Regression	1.00	5113240242699.29	5113240242699.29	27.95	0.00
	Residual	28.00	5122876885043.37	182959888751.55
	Total	29.00	10236117127742.70
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
	Intercept	1196918.81	251124.06	4.77	0.00	682514.49	1711323.13	682514.49	1711323.13
	Team Salary	10347.29	1957.30	5.29	0.00	6337.95	14356.63	6337.95	14356.63
	RESIDUAL OUTPUT					PROBABILITY OUTPUT
	Observation	Predicted Attendance	Residuals	Standard Residuals		Percentile	Attendance
	1.00	1877770.48	202374.52	0.48		1.67	1287054.00
	2.00	2124035.98	-122643.98	-0.29		5.00	1388905.00
	3.00	2427211.57	-146009.57	-0.35		8.33	1752235.00
	4.00	2942506.61	-61812.61	-0.15		11.67	1755810.00
	5.00	2409621.18	550190.82	1.31		15.00	1768175.00
	6.00	2342363.80	-586553.80	-1.40		18.33	1831080.00
	7.00	2414794.82	4711.18	0.01		21.67	2001392.00
	8.00	2104376.13	-715471.13	-1.70		25.00	2080145.00
	9.00	2214057.40	292731.60	0.70		28.33	2153585.00
	10.00	2984930.50	-258882.50	-0.62		31.67	2193581.00
	11.00	1911916.54	241668.46	0.57		35.00	2220054.00
	12.00	2365127.83	343421.17	0.82		38.33	2281202.00
	13.00	2711762.04	301002.96	0.72		41.67	2419506.00
	14.00	3580934.39	183880.61	0.44		45.00	2459742.00
	15.00	2072299.53	-320064.53	-0.76		48.33	2491875.00
	16.00	2218196.32	324361.68	0.77		51.67	2498596.00
	17.00	2317530.30	-97476.30	-0.23		55.00	2506789.00
	18.00	2232682.52	337070.48	0.80		58.33	2542558.00
	19.00	3406065.19	-212270.19	-0.51		61.67	2569753.00
	20.00	2032979.83	-264804.83	-0.63		65.00	2619843.00
	21.00	2573108.36	-742028.36	-1.77		68.33	2708549.00
	22.00	2085751.01	412844.99	0.98		71.67	2726048.00
	23.00	2506885.70	-47143.70	-0.11		75.00	2794891.00
	24.00	2919742.57	456139.43	1.09		78.33	2880694.00
	25.00	2471704.92	-278123.92	-0.66		81.67	2959812.00
	26.00	2441697.78	1079191.22	2.57		85.00	3012765.00
	27.00	1970896.09	-683842.09	-1.63		88.33	3193795.00
	28.00	2695206.38	-203331.38	-0.48		91.67	3375882.00
	29.00	2401343.35	393547.65	0.94		95.00	3520889.00
	30.00	3002520.89	-382677.89	-0.91		98.33	3764815.00
Sheet2
	
Attendance
Predicted Attendance
Team Salary
Attendance
Team Salary Line Fit  Plot
Chapter 13 – Problem 63
	
												Team	League	Opened	Team Salary	Attendance	Wins	ERA	BA	HR				Year	Average Salary
												Arizona	National	1998	65.80	2080145	79	4.04	0.264	154				2000	1.99
												Atlanta	National	1996	89.60	2001392	67	4.41	0.251	100				2001	2.26
												Baltimore	American	1992	118.90	2281202	81	4.05	0.25	217				2002	2.38
												Boston	American	1912	168.70	2880694	78	4.31	0.265	161				2003	2.56
												Chicago Cubs	National	1914	117.20	2959812	97	3.36	0.244	171				2004	2.49
												Chicago White Sox	American	1991	110.70	1755810	76	3.98	0.25	136				2005	2.63
												Cincinnati	National	2003	117.70	2419506	64	4.33	0.248	167				2006	2.87
												Cleveland	American	1994	87.70	1388905	81	3.67	0.256	141				2007	2.94
												Colorado	National	1995	98.30	2506789	68	5.04	0.265	186				2008	3.15
												Detroit	American	2000	172.80	2726048	74	4.64	0.27	151				2009	3.24
												Houston	American	2000	69.10	2153585	86	3.57	0.25	230				2010	3.3
												Kansas City	American	1973	112.90	2708549	95	3.73	0.269	139				2011	3.31
												LA Angels	American	1966	146.40	3012765	85	3.94	0.246	176				2012	3.44
												LA Dodgers	National	1962	230.40	3764815	92	3.44	0.25	187				2013	3.65
												Miami	National	2012	84.60	1752235	71	4.02	0.26	120				2014	3.95
												Milwaukee	National	2001	98.70	2542558	68	4.28	0.251	145				2015	4.25
												Minnesota	American	2010	108.30	2220054	83	4.07	0.247	156				2016	4.4
												NY Mets	National	2009	100.10	2569753	90	3.43	0.244	177
												NY Yankees	American	2009	213.50	3193795	87	4.05	0.251	212			att
												Oakland	American	1966	80.80	1768175	68	4.14	0.251	146		10347.2898751388
												Philadelphia	National	2004	133.00	1831080	63	4.69	0.249	130
												Pittsburgh	National	2001	85.90	2498596	98	3.21	0.26	140
												San Diego	National	2004	126.60	2459742	74	4.09	0.243	148
												San Francisco	National	2000	166.50	3375882	84	3.72	0.267	136
												Seattle	American	1999	123.20	2193581	76	4.16	0.249	198
	What is the expected attendance for a team with a salary of $100.0 million?											St. Louis	National	2006	120.30	3520889	100	2.94	0.253	137
	2231618											Tampa Bay	American	1990	74.80	1287054	80	3.74	0.252	167
												Texas	American	1994	144.80	2491875	88	2.24	0.257	172
	If the owners pay an additional $30 million, how many more people could they ex-pect to attend?											Toronto	American	1989	116.40	2794891	93	3.8	0.269	232
	310410											Washington	National	2008	174.50	2619843	83	3.62	0.251	177
	What percentage of the variation in attendance is accounted for by salary?
	0.499			correlation between attendance and team batting average
				0.1240653521
				be-tween attendance and team ERA.
				-0.2571981867
	SUMMARY OUTPUT
	Regression Statistics
	Multiple R	0.71
	R Square	0.50
	Adjusted R Square	0.48
	Standard Error	427738.11
	Observations	30.00
	ANOVA
		df	SS	MS	F	Significance F
	Regression	1.00	5113240242699.29	5113240242699.29	27.95	0.00
	Residual	28.00	5122876885043.37	182959888751.55
	Total	29.00	10236117127742.70
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
	Intercept	1196918.81	251124.06	4.77	0.00	682514.49	1711323.13	682514.49	1711323.13
	Team Salary	10347.29	1957.30	5.29	0.00	6337.95	14356.63	6337.95	14356.63
Refer to the Baseball 2016 data, which reports information on the 2016 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. 
Determine the regression equation and answer the following questions.a. Draw a scatter diagram. From the diagram, does there seem to be a direct relation-ship between the two variables?
 b. What is the expected attendance for a team with a salary of $100.0 million?
 c. If the owners pay an additional $30 million, how many more people could they ex-pect to attend? 
d. At the .05 significance level, can we conclude that the slope of the regression line is positive? Conduct the appropriate test of hypothesis.
 e. What percentage of the variation in attendance is accounted for by salary? f. Determine the correlation between attendance and team batting average and be-tween attendance and team ERA. Which is stronger? Conduct an appropriate test of hypothesis for each set of variables.
Chapter 13 – Problem 63
	
team salary
Attendance
Trend line
y = 10347x + 1E+06
R² = 0.499
Bus maintenance 
	
Attendance
Predicted Attendance
Team Salary
Attendance
Team Salary Line Fit  Plot
Chapter 13 – Problem 64
	
Sheet7
	
Sheet1
	SUMMARY OUTPUT
	Regression Statistics
	Multiple R	0.7075670557
	R Square	0.5006511383
	Adjusted R Square	0.4942492299
	Standard Error	1658.0967315122
	Observations	80
	ANOVA
		df	SS	MS	F	Significance F
	Regression	1	215003471.845492	215003471.845492	78.2034200711	0
	Residual	78	214444212.142008	2749284.77105139
	Total	79	429447683.9875
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
	Intercept	337.2967490852	511.3722604612	0.6595914076	0.5114589185	-680.7671999274	1355.3606980978	-680.7671999274	1355.3606980978
	Age	603.1614670361	68.2057070877	8.8432697613	0	467.3743372449	738.9485968273	467.3743372449	738.9485968273
	RESIDUAL OUTPUT					PROBABILITY OUTPUT
	Observation	Predicted Maintenance Cost	Residuals	Standard Residuals		Percentile	Maintenance Cost
	1	3353.1040842657	1292.8959157343	0.7847294376		0.625	505
	2	1543.6196831574	-471.6196831574	-0.2862518508		1.875	1008
	3	6368.9114194463	3025.0885805537	1.8360921645		3.125	1061
	4	1543.6196831574	-465.6196831574	-0.2826101217		4.375	1072
	5	1543.6196831574	-535.6196831574	-0.3250969607		5.625	1078
	6	3353.1040842657	1975.8959157343	1.1992795953		6.875	1569
	7	6368.9114194463	-1574.9114194463	-0.9559001133		8.125	1826
	8	5162.5884853741	-1210.5884853741	-0.7347725441		9.375	1881
	9	4559.427018338	-817.427018338	-0.4961412876		10.625	1955
	10	5765.7499524102	-1389.7499524102	-0.8435154642		11.875	2028
	11	6368.9114194463	-1536.9114194463	-0.9328358293		13.125	2116
	12	6368.9114194463	-1208.9114194463	-0.7337546408		14.375	2152
	13	2749.9426172296	-794.9426172296	-0.4824942714		15.625	2356
	14	3956.2655513018	-1181.2655513019	-0.7169748472		16.875	2470
	15	3956.2655513018	1395.7344486981	0.8471477832		18.125	2540
	16	3956.2655513018	-891.2655513018	-0.5409579428		19.375	2732
	17	2146.7811501935	996.2188498065	0.6046598556		20.625	2775
	18	2146.7811501935	-577.7811501935	-0.3506870673		21.875	2985
	19	5162.5884853741	2603.4115146259	1.5801532272		23.125	3011
	20	5162.5884853741	-1419.5884853741	-0.8616261063		24.375	3065
	21	2146.7811501935	393.2188498065	0.2386660853		25.625	3097
	22	5765.7499524102	-1423.7499524102	-0.8641519289		26.875	3124
	23	4559.427018338	-1198.4270183379	-0.7273910828		28.125	3143
	24	2146.7811501935	950.2188498065	0.5767399328		29.375	3173
	25	5765.7499524102	2497.2500475898	1.5157180106		30.625	3190
	26	5162.5884853741	-944.5884853741	-0.5733225559		31.875	3213
	27	2749.9426172296	-721.9426172296	-0.4381865679		33.125	3361
	28	3956.2655513018	1864.7344486981	1.1318096046		34.375	3527
	29	5765.7499524102	3303.2500475898	2.0049236141		35.625	3560
	30	3956.2655513018	-945.2655513018	-0.5737335043		36.875	3656
	31	5765.7499524102	3427.2500475898	2.0801860146		38.125	3690
	32	5765.7499524102	-970.7499524102	-0.589201385		39.375	3742
	33	940.4582161213	-435.4582161213	-0.2643034732		40.625	3743
	34	3956.2655513018	-1224.2655513019	-0.7430739055		41.875	3754
	35	5162.5884853741	-1408.5884853741	-0.854949603		43.125	3769
	36	5765.7499524102	-1125.7499524102	-0.6832793856		44.375	3770
	37	5765.7499524102	2644.2500475898	1.6049403725		45.625	3809
	38	6972.0728864824	-1050.0728864824	-0.637346824		46.875	3920
	39	5765.7499524102	-1401.7499524102	-0.8507989223		48.125	3952
	40	4559.427018338	-1369.4270183379	-0.8311803609		49.375	4139
	41	3956.2655513018	-743.2655513018	-0.451128626		50.625	4218
	42	5765.7499524102	-1626.7499524102	-0.987363762		51.875	4279
	43	4559.427018338	-999.427018338	-0.606607069		53.125	4342
	44	5162.5884853741	-1242.5884853741	-0.7541950991		54.375	4364
	45	5162.5884853741	1570.4115146259	0.9531688743		55.625	4376
	46	5162.5884853741	-1392.5884853741	-0.8452383255		56.875	4513
	47	6368.9114194463	-1200.9114194463	-0.7288990021		58.125	4563
	48	8781.5572875907	-1401.5572875907	-0.8506819835		59.375	4640
	49	2749.9426172296	906.0573827704	0.5499359165		60.625	4646
	50	3956.2655513018	2256.7344486982	1.369735903		61.875	4723
	51	2749.9426172296	1529.0573827704	0.9280687837		63.125	4752
	52	6368.9114194463	4206.0885805537	2.5529058341		64.375	4794
	53	5765.7499524102	-1013.7499524102	-0.6153004432		65.625	4795
	54	5162.5884853741	-1353.5884853741	-0.8215670866		66.875	4832
	55	4559.427018338	-790.427018338	-0.4797535068		68.125	5160
	56	2749.9426172296	-597.9426172296	-0.3629241674		69.375	5168
	57	3956.2655513018	-971.2655513018	-0.5895143302		70.625	5284
	58	5765.7499524102	-1202.7499524102	-0.7300149085		71.875	5329
	59	6368.9114194463	-1645.9114194463	-0.9989939072		73.125	5352
	60	2749.9426172296	-923.9426172296	-0.5607914462		74.375	5408
	61	1543.6196831574	-482.6196831574	-0.292928354		75.625	5821
	62	2749.9426172296	777.0573827704	0.4716387418		76.875	5922
	63	6368.9114194463	3300.0885805537	2.0030047463		78.125	5976
	64	2749.9426172296	-633.9426172296	-0.3847745417		79.375	6212
	65	7575.2343535185	-1363.2343535185	-0.827421693		80.625	6213
	66	4559.427018338	2367.5729816621	1.4370098874		81.875	6733
	67	1543.6196831574	337.3803168426	0.2047746172		83.125	6863
	68	4559.427018338	2444.5729816621	1.4837454103		84.375	6927
	69	6368.9114194463	-1084.9114194463	-0.6584922403		85.625	7004
	70	4559.427018338	-1386.4270183379	-0.8414985933		86.875	7380
	71	6368.9114194463	3764.0885805537	2.2846317935		88.125	7766
	72	3353.1040842657	-997.1040842657	-0.6051971529		89.375	8263
	73	3956.2655513018	-832.2655513018	-0.505147607		90.625	8410
	74	3956.2655513018	2019.7344486981	1.2258876052		91.875	9069
	75	6972.0728864824	-1564.0728864824	-0.9493216133		93.125	9193
	76	4559.427018338	-869.427018338	-0.5277029394		94.375	9394
	77	6368.9114194463	3204.0885805537	1.9447370814		95.625	9573
	78	3353.1040842657	-883.1040842657	-0.5360043008		96.875	9669
	79	5162.5884853741	1700.4115146259	1.0320730039		98.125	10133
	80	5765.7499524102	-1252.7499524102	-0.7603626507		99.375	10575
Sheet1
	
Maintenance Cost
Predicted Maintenance Cost
Age
Maintenance Cost
Age Line Fit  Plot
Sheet3
	
											ID	Manufacturer	Engine Type (0=diesel)	Capacity	Age	Maintenance Cost	Odometer Miles	Miles
											10	Keiser	1	14	5	4646	54375	11973
											396	Thompson	0	14	2	1072	21858	11969
											122	Bluebird	1	55	10	9394	116580	11967
											751	Keiser	0	14	2	1078	22444	11948
											279	Bluebird	0	55	2	1008	22672	11925
											500	Bluebird	1	55	5	5329	50765	11922
											520	Bluebird	0	55	10	4794	119130	11896
											759	Keiser	0	55	8	3952	87872	11889
											714	Bluebird	0	42	7	3742	73703	11837
											875	Bluebird	0	55	9	4376	97947	11814
	see below.

Complete the problems below from the textbook. You will need to use the "Baseball 2016 Data," "Lincolnville School District Bus Data," and the "Century National Bank Data" files for this...

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