You may need to use the appropriate technology to answer this question.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	6,250
C	14.9	8,370
D	15.9	6,200
E	17.2	4,000
F	13.1	8,600
G	16.2	6,000
H	17.1	2,580
I	17.6	3,300
J	14.1	8,000

These data provided the estimated regression equation

= 28,682 1,446x.

For these data, SSE = 7,080,262.93 and SST = 52,559,800. Use the F 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.

H₀: ₀ = 0 H_a: ₀ 0

H₀: ₁ = 0 H_a: ₁ 0

H₀: ₁ 0 H_a: ₁ = 0

H₀: ₁ 0 H_a: ₁ < 0

H₀: ₀ 0 H_a: ₀ = 0

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

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

p-value =

State your conclusion.

Do not reject H₀. We conclude that the relationship between weight (pounds) and price ($) is significant.

Reject H₀. We conclude that the relationship between weight (pounds) and price ($) is significant.

Do not reject H₀. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.

Reject H₀. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.