Consider the following data on x = weight (pounds) and y = price (s) 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 8,700 G 16.2 6,000 H 17.1 2,680 1 17.6 3,500 J 14.1 8,000 These data provided the estimated regression equation ý= 28,621 1,439x. For these data, SSE = 6,824,137.81 and SST = 51,870,800. Use the F test to determine whether the weight for a bike and the price are related at the 0.05 level of signifi State the null and alternative hypotheses. O Ho: Bo=0 H₂: Bo = 0 O Ho: B₂ 20 H₂: B₂ <0 OH: 6.10

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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.
O Reject Ho. We conclude that the relationship between weight (pounds) and price ($) is significant.
O Reject Ho. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.
O Do not reject Ho. We conclude that the relationship between weight (pounds) and price ($) is significant.
O Do not reject Ho. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.
Transcribed Image Text: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. O Reject Ho. We conclude that the relationship between weight (pounds) and price ($) is significant. O Reject Ho. We cannot conclude that the relationship between weight (pounds) and price ($) is significant. O Do not reject Ho. We conclude that the relationship between weight (pounds) and price ($) is significant. O Do not reject Ho. We cannot conclude that the relationship between weight (pounds) and price ($) is significant.
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
17.2
4,000
13.1
8,700
16.2
6,000
H
17.1
2,680
I
17.6
3,500
J
14.1
8,000
These data provided the estimated regression equation ý = 28,621 - 1,439x. For these data, SSE = 6,824,137.81 and SST = 51,870,800. 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.
O Ho: Bo = 0
Ha: Bo = 0
O Ho: B₁ 20
H₂: B₁ <0
O Ho: B₁ * 0
H₂: B₁ = 0
O Ho: Bo #0
Ha: Bo = 0
O Ho: B₁ = 0
H₂: B₁ * 0
Find the value of the test statistic. (Round your answer to two decimal places.)
Find the n-value (Round your answer to three decimal places)
IT m
Transcribed Image Text: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 17.2 4,000 13.1 8,700 16.2 6,000 H 17.1 2,680 I 17.6 3,500 J 14.1 8,000 These data provided the estimated regression equation ý = 28,621 - 1,439x. For these data, SSE = 6,824,137.81 and SST = 51,870,800. 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. O Ho: Bo = 0 Ha: Bo = 0 O Ho: B₁ 20 H₂: B₁ <0 O Ho: B₁ * 0 H₂: B₁ = 0 O Ho: Bo #0 Ha: Bo = 0 O Ho: B₁ = 0 H₂: B₁ * 0 Find the value of the test statistic. (Round your answer to two decimal places.) Find the n-value (Round your answer to three decimal places) IT m
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