Question

This is the third time I've had to post this because the answers I've been getting have been incorrect. All of the answers that are filled in are correct. please help if you can

Despite the growth in digital entertainment, the nation's 400 amusement parks have managed to hold on to visitors. A manager collects data on the number of visitors (in millions) to amusement parks in the United States. A portion of the data is shown in the accompanying table. Year 2009 2001 Visitors 323 329 2007 325 SOURCE: International Association of Amusement Parks and Attractions. picture Click here for the Excel Data File b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Exponential Trend Variable Intercept Linear Trend 349.21 -3.55 25.92 t -0.01 0.08 Standard Error b-2. Calculate the MSE for both trends. (Do not round estimates ot intermediate calculations. Round final answers to 2 decimal places.) Linear Trend Exponential Trend MSE

Answer 1

Year	t	visitors(Y)	ln(Y)
2000	1	323	5.777652
2001	2	329	5.796058
2002	3	368	5.908083
2003	4	378	5.934894
2004	5	321	5.771441
2005	6	308	5.7301
2006	7	314	5.749393
2007	8	325	5.783825

Linear model: (t and Y)

Excel > Data > Data Analysis > Regression

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.340488943
R Square	0.11593272
Adjusted R Square	-0.031411826
Standard Error	25.91944174
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	1	528.5952381	528.5952381	0.786813784	0.409209379
Residual	6	4030.904762	671.8174603
Total	7	4559.5
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	349.2142857	20.1962663	17.29103195	2.39729E-06	299.7958024	398.6327691	299.7958024	398.6327691
t	-3.547619048	3.99945669	-0.887025244	0.409209379	-13.33393702	6.238698926	-13.33393702	6.238698926

Y^ = 349.21-3.55*t

Exponential model: (t and LN(Y))

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.348579763
R Square	0.121507851
Adjusted R Square	-0.024907507
Standard Error	0.075164516
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	1	0.004688603	0.004688603	0.829884603	0.397426984
Residual	6	0.033898227	0.005649705
Total	7	0.03858683
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	5.853976304	0.058567719	99.95226676	6.7587E-11	5.710666257	5.99728635	5.710666257	5.99728635
year	-0.010565671	0.011598137	-0.910980023	0.397426984	-0.038945289	0.017813947	-0.038945289	0.017813947

Ln(Y) = 5.8540-0.01*t

Y = e^(5.8540-0.01*t)

Y = 348.62*e^(-0.01*t)

b-1)

	Linear model	Exponential model
Intercept	349.21	348.62
year	-3.55	-0.01
Standard Error	25.92	0.08

b-2)

	Linear model	Exponential model
MSE	671.82	0.01