Consider the following data on x = weight (pounds) andy = 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 | 8,500 |
| G | 16.2 | 6,000 |
| H | 17.1 | 2,580 |
| I | 17.6 | 3,500 |
| J | 14.1 | 8,000 |
These data provided the estimated regression equation
ŷ = 28,243 − 1,418x.
For these data, SSE = 7,368,713.71 and SST = 51,100,800. Use theF test to determine whether the weight for a bike and theprice are related at the 0.05 level of significance.
State the null and alternative hypotheses.
H0: β0 ≠0
Ha: β0 =0H0: β1 ≠0
Ha: β1 =0    H0:β0 = 0
Ha: β0 ≠0H0: β1 = 0
Ha: β1 ≠0H0: β1 ≥ 0
Ha: β1 < 0
Find the value of the test statistic. (Round your answer to twodecimal places.)
Find the p-value. (Round your answer to three decimalplaces.)
p-value =
State your conclusion.
Reject H0. We cannot conclude that therelationship between weight (pounds) and price ($) issignificant.Do not reject H0. We conclude thatthe relationship between weight (pounds) and price ($) issignificant.    Do not rejectH0. We cannot conclude that the relationshipbetween weight (pounds) and price ($) is significant.RejectH0. We conclude that the relationship betweenweight (pounds) and price ($) is significant.
