A researcher analyzes the relationship between amusement park attendance and the price of admission. She estimates the following model: Attendance = β0 + β1 Price + ε, where Attendance is the daily attendance (in 1,000s) and Price is the gate price (in $). A portion of the regression results is shown in the accompanying table.
df 
SS 
MS 
F 

Regression 
1 
19,744.99 
19,744.99 
44.79 
Residual 
28 
12,343.78 
440.85 

Total 
29 
32,088.78 

Coefficients 
Standard Error 
tstat 
pvalue 

Intercept 
416.3 
38.84 
8.61 
2.32E09 
Price 
4.35 
0.46 
6.69 
2.9E07 
Predict the Attendance for an amusement park that charges $80 for admission.
(no excel work)
Solution:
ANOVA table and Coefficient correlation table is given in the
question
From Coefficient correlation table we can write Regression equation
as follows
Attendance = 416.3  4.35*Price
Here Intercept of regression line = 416.3
Slope of regression line = 4.35
As the price increase by 1 unit than Attendance will decrease by
4.35 unit.
If X = 80 than
Attendance = 416.3  4.35*Price = 416.3  4.35*80 = 416.3  348 =
68.3
the Attendance for an amusement park that charges $80 for
admission is (68.3*1000) = 68300
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