Question

Use the Regression tool on the accompanying wedding data, using the wedding cost as the dependent variable and attendance as the independent variable. Complete parts a through c. Click the icon to view the wedding data. a. What is the regression model? Wedding Cost =+Attendance (Round to three decimal places as needed.) b. Interpret all key regression results, hypothesis tests, and confidence intervals in the regression output from part a. Interpret the slope of the regression equation. Choose the correct answer below. O A. It is not appropriate to interpret the slope because it is outside the range of observed wedding costs. OB. The slope indicates that for each increase of 1 in wedding cost, the predicted attendance is estimated to increase by a value equal to ba OC. It is not appropriate to interpret the slope because it is outside the range of observed attendances OD. The slope indicates that for each increase of 1 in attendance, the predicted wedding cost is estimated to increase by a value equal to by Interpret the Y-intercept of the regression equation. Choose the correct answer below. O A. It is not appropriate to interpret the Y-intercept because it is outside the range of observed attendances. O B. The Y-intercept indicates that a wedding with an attendance of 0 people has a mean predicted cost of Sbo O C. The Y-intercept indicates that a wedding with a cost of $0 has a mean predicted attendance of bo people.

Answer 1

S.No х Y (y-7) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Total 300 350 150 200 250 150 250 300 250 200 150 200 200 200 200 200 150 200 150 100 100 150 50 50 4500 187.500 59700 53000 48000 41000 36000 32500 29000 28000 26000 26000 25000 25000 24000 24000 21000 18000 17000 17000 17000 16000 13000 11000 9000 3000 619200 (x-x)? 12656.2500 26406.2500 1406.2500 156.2500 3906.2500 1406.2500 3906.2500 12656.2500 3906.2500 156.2500 1406.2500 156.2500 156.2500 156.2500 156.2500 156.2500 1406.2500 156.2500 1406.2500 7656.2500 7656.2500 1406.2500 18906.2500 18906.2500 126250.0000 SSX 1149210000.00 739840000.00 492840000.00 231040000.00 104040000.00 44890000.00 10240000.00 4840000.00 40000.00 40000.00 640000.00 640000.00 3240000.00 3240000.00 23040000.00 60840000.00 77440000.00 77440000.00 77440000.00 96040000.00 163840000.00 219040000.00 282240000.00 519840000.00 4381980000.0000 (X-X)(y-7) 3813750.0000 4420000.0000 -832500.0000 190000.0000 637500.0000 -251250.0000 200000.0000 247500.0000 12500.0000 2500.0000 30000.0000 - 10000.0000 -22500.0000 -22500.0000 -60000.0000 -97500.0000 330000.0000 -110000.0000 330000.0000 857500.0000 1120000.0000 555000.0000 2310000.0000 3135000.0000 16785000.0000 Mean 25800.0000 SSY SXY sample size : 24 126250.000 S, 187.5000 y = 25800.0000 San (X-X)2= Sw (X-X)(y-7)= slope B. 5./5.- intercepta ßo = -B,x= 16785000.000 132.95050 Sy Cov= 871.78218

a)

Wedding cost =871.782+132.950*x

b_)

OD. The slope indicates that for each increase of 1 in attendance, the predicted wedding cost is estimated to increase by a value equal to by.

O A. It is not appropriate to interpret the Y-intercept because it is outside the range of observed attendances.

option C is correct

C .Coefficient of determination R2=SSR/SST=

0.509, proportion of variation explained in wedding cost

correlation r='Sxy/(√Sxx*Syy) =		0.714
test stat t=	r*(√(n-2)/(1-r2))=	4.78
P value    =	0.000	(from excel:tdist(4.7781,22,2)

reject Ho . there is sufficient evidence,,,,,,,

the confidence interval is 75.245 < ß1 <190.656 , with 95% confidence,

c_)

predicted val=871.782+225*132.95=30786