Question

For major league baseball teams, is there a relationship between player payrolls and gate money? Here are data for each of the American League teams for the year 2001. The variable x denotes the 2001 player payroll (in millions of dollars), and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the Figure 1 scatter plot. Also given are the products of the player payroll values and mean attendance values for each of the fourteen teams. These products, written in the column labelled "xy," may aid in calculations.) ху Player payroll, x Mean (in $1,000,000 attendance, y s) (in thousands) 46.6 24.69 73.4 38.15 109.6 32.47 45 1150.554 2800.21 3558.712 40 62.4 35- 21.85 1363.44 30 25- 92.0 49.8 35.6 24.4 39.26 23.70 19.01 21.98 3611.92 1180.26 676.756 536.312 20 15 Anaheim Baltimore Boston Chicago White Sox Cleveland Detroit Kansas City Minnesota New York Yankees Oakland Seattle Tampa Bay Texas Toronto Send data to Excel 109.8 40.25 4419.45 10- 5+ 33.8 75.7 55.0 88.5 75.8 26.54 43.33 16.05 34.94 23.70 0 897.052 3280.081 882.75 3092.19 1796.46 20 as o + 80 100 120 10 Figure 1 Answer the following. Carry your intermediate computations to at least four decimal places, and round your answer as specified below. regression line for these data? Round your answer to at a least two decimal places.

Answer 1

	X	Y	X^2	Y^2	XY
	46.6	24.69	2171.56	609.5961	1150.554
	73.4	38.15	5387.56	1455.423	2800.21
	109.6	32.47	12012.16	1054.301	3558.712
	62.4	21.85	3893.76	477.4225	1363.44
	92	39.26	8464	1541.348	3611.92
	49.8	23.7	2480.04	561.69	1180.26
	35.6	19.01	1267.36	361.3801	676.756
	24.4	21.98	595.36	483.1204	536.312
	109.8	40.25	12056.04	1620.063	4419.45
	33.8	26.54	1142.44	704.3716	897.052
	75.7	43.33	5730.49	1877.489	3280.081
	55	16.05	3025	257.6025	882.75
	88.5	34.94	7832.25	1220.804	3092.19
	75.8	23.7	5745.64	561.69	1796.46
SUM	932.4	405.92	71803.66	12786.3	29246.147
n	14
Mean	66.6	28.99428571
k	2
SSxx	9705.82	Sum(x^2) - ((Sum(x))^2 /n)
SSyy	1016.939	Sum(y^2) - ((Sum(y))^2 /n)
SSxy	2211.875	Sum(xy) - (Sum(x)*Sum(y)/n)
slope	0.227892	SSxy/SSxx
intercept	13.8167	Mean Y - Mean X * Slope

Slope of the regression line = 0.23