A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y =B₁ + B₁x + 8 where y = traffic flow in vehicles per hour x = vehicle speed in miles per hour. The following data were collected during rush hour for six highways leading out of the city. Traffic Flow Vehicle Speed (y) (x) 1,257 35 1,330 40 1,225 30 1,334 45 1,348 50 1,126 25 In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation. ŷ = bo + b₁x + b₂x² (a) Develop an estimated regression equation for the data of the form ý = bo + b₂x + b₂x². (Round bo to the nearest integer and b₁ to two decimal places and b₂ to three decimal places.) ý =

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(b) Use a = 0.01 to test for a significant relationship.
State the null and alternative hypotheses.
Ho: bo = b₁ = b ₂ = 0
H₂: One or more of the parameters is not equal to zero.
O Ho: One or more of the parameters is not equal to zero.
Ha: bo=b₁ = b ₂ = 0
O Ho: One or more of the parameters is not equal to zero.
Ha: b₁ b₂ = 0
ⒸH₁: b₁ = b ₂ = 0
H₂: One or more of the parameters is not equal to zero.
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 =
What is your conclusion?
O Reject Ho. We cannot conclude that the relationship is significant.
Do not reject Ho. We conclude that the relationship is significant.
O Reject Ho. We conclude that the relationship is significant.
O Do not reject Ho. We cannot conclude that the relationship is significant.
(c) Base on the model predict the traffic flow in vehicles per hour at a speed of 38 miles per hour. (Round your answer to two decimal places.)
vehicles per hour
Transcribed Image Text:(b) Use a = 0.01 to test for a significant relationship. State the null and alternative hypotheses. Ho: bo = b₁ = b ₂ = 0 H₂: One or more of the parameters is not equal to zero. O Ho: One or more of the parameters is not equal to zero. Ha: bo=b₁ = b ₂ = 0 O Ho: One or more of the parameters is not equal to zero. Ha: b₁ b₂ = 0 ⒸH₁: b₁ = b ₂ = 0 H₂: One or more of the parameters is not equal to zero. 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 = What is your conclusion? O Reject Ho. We cannot conclude that the relationship is significant. Do not reject Ho. We conclude that the relationship is significant. O Reject Ho. We conclude that the relationship is significant. O Do not reject Ho. We cannot conclude that the relationship is significant. (c) Base on the model predict the traffic flow in vehicles per hour at a speed of 38 miles per hour. (Round your answer to two decimal places.) vehicles per hour
A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized:
y =B₁ + B₁x + 8
where
y = traffic flow in vehicles per hour
x = vehicle speed in miles per hour.
The following data were collected during rush hour for six highways leading out of the city.
Traffic Flow Vehicle Speed
(y)
(x)
1,257
35
1,330
40
1,225
30
1,334
45
1,348
50
1,126
25
In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation.
ŷ = bo + b₂x + b₂x²
(a) Develop an estimated regression equation for the data of the form ý = bo + b₁x + b₂x². (Round bo to the nearest integer and b₁ to two decimal places and b₂ to three decimal places.)
Transcribed Image Text:A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y =B₁ + B₁x + 8 where y = traffic flow in vehicles per hour x = vehicle speed in miles per hour. The following data were collected during rush hour for six highways leading out of the city. Traffic Flow Vehicle Speed (y) (x) 1,257 35 1,330 40 1,225 30 1,334 45 1,348 50 1,126 25 In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation. ŷ = bo + b₂x + b₂x² (a) Develop an estimated regression equation for the data of the form ý = bo + b₁x + b₂x². (Round bo to the nearest integer and b₁ to two decimal places and b₂ to three decimal places.)
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