Consider the following data on x = weight (pounds) and y = price ($) for 10 road-racing bikes. Brand Weight Price ($) A 17.8 2,100 B 16.1 6,350 C 14.9 8,370 D 15.9 6,200 E 17.2 4,000 F 13.1 8,600 G...


Consider the following data onx = weight (pounds) andy = price ($) for 10 road-racing bikes.



























































BrandWeightPrice ($)
A17.82,100
B16.16,350
C14.98,370
D15.96,200
E17.24,000
F13.18,600
G16.26,000
H17.12,480
I17.63,400
J14.18,000

These data provided the estimated regression equation
ŷ = 28,648 − 1,444x.

For these data, SSE = 7,568,661.27 and SST = 52,874,800. Use theF test to determine whether the weight for a bike and the price are related at the 0.05 level of significance.

State the null and alternative hypotheses.



H
0: ?1 = 0

H
a: ?1 ≠ 0



H
0: ?1 ≠ 0

H
a: ?1
= 0



H
0: ?1 ≥ 0

H
a: ?1 <>



H
0: ?0 ≠ 0

H
a: ?0 = 0



H
0: ?0 = 0

H
a: ?0 ≠ 0


Find the value of the test statistic. (Round your answer to two decimal places.)


Find thep-value. (Round your answer to three decimal places.)


p-value =

State your conclusion.


Do not rejectH
0. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.

Do not rejectH
0. We conclude that the relationship between weight (pounds) and price ($) is significant.

RejectH
0. We conclude that the relationship between weight (pounds) and price ($) is significant.

RejectH
0. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.



Jun 07, 2022
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