1. The front office of the Oklahoma City Dodgers would like to predict game attendance using the temperature. A random s

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1. The front office of the Oklahoma City Dodgers would like to
predict game attendance using the temperature. A random sample of
25 games produced the following regression equation:
yˆ = 6000 − 15x Also, assume that SSR = 42400 and SSE = 24600.
(a) Find and interpret the coeffcient of determination.
r^2 = 0.6328, temperature explains 63.28% of the variance in
attendance
(b) Conduct a test to determine if there is a significant negative
correlation between attendance and temperature using α =
0.05.
H0 :ρ=0 H1 :ρ<0
TS: t = −6.30 RR: t∗ = −1.714
Reject H0
(c) Interpret the values of βˆ0 and βˆ1 in the context of the
problem.
βˆ0 : expected mean attendance is 6000 when temperature equals
0
βˆ1 : mean attendance decreases by 15 for each additional degree of
temperature
2. The FTC measured the amount of tar (in mg) and carbon monoxide
(in mg) per cigarette for all domestic cigarettes. A sample of 12
brands yielded the following data.
Brand
X Y
Capri
9 6
carlton
4 6
kent
14 14
kool mild 12
12
Marlboro Light 10 12
Merit Ultra 5
7
now
3 4
salem 17
18
triumph 6
8
true
7 8
vantage 8
13
virginia slim. 15
13
Note: the value of the correlation coe􏰁cient is 0.8905, x ̄ =
9.167, y ̄ = 10.083, Sx = 4.529, and
Sy = 4.166.
(a) Find the regression equation for predicting the amount of
carbon monoxide from the amount of tar in a cigarette.
yˆ = 2.575 + 0.819x
(b) Interpret the values of βˆ0 and βˆ1 in the context of the
problem.
βˆ0 : expected mean CO is 2.575 mg when tar equals 0 mg
βˆ1 : mean CO increases by 0.819 mg for each additional mg of
tar
(c) Find a 95% prediction interval for the amount of carbon
monoxide for a cigarette that contains 8 mg of tar. Note that
spred= 2.075.
9.128 ± 2.228(2.075)
(d) Compute the residual for Marlboro Light.
e = 1.234