To determine whether extra personnel are needed for the day, the owners of a water adventure park would like to find a model that would allow them to predict the day's attendance each morning before opening based on the day of the week and weather conditions. The model is of the form
E(y) = β0 + β1x1 + β2x2 + β3x3
Where

These data were recorded for a random sample of 30 days, and a regression model was fitted to the data. The least squares analysis produced the following results:
= -105 + 25x1 + 100x2 + 10x3
with
s1= 10 s2 = 30 s3 = 4 R2 = .65
a. Interpret the estimated model coefficients.
b. Is there sufficient evidence to conclude that this model is useful for the prediction of daily attendance? Use a = .05.
c. Is there sufficient evidence to conclude that the mean attendance increases on weekends? Use a = .10.
(I.
d. Use the model to predict the attendance on a sunny weekday with a predicted high temperature of 95°F.
e. Suppose the 90% prediction interval for part d is (645, 1,245).

Transcribed Image Text:

yDaily admission ri# {1 İtherwend (dummy variable) 0 otherwise 1 if sunny 0 if overcast (dummy variable) predicted daily high temperature (°F)