A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized:y = Po + BqX + Ewherey = traffic flow in vehicles per hourx = vehicle speed in miles per hour.The following data were collected during rush hour for six highways leading out of the city.Vehicle Speed(x)Traffic Flow(y)1,258351,330401,225301,336451,347501,12425In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation.ŷ = bo + bqx + bx²(a) Develop an estimated regression equation for the data of the form ŷ = b, + b,x + b,x². (Round b, to the nearest integer and b, to two decimal places and b, to three decimal places.)1(b) Use a = 0.01 to test for a significant relationship.State the null and alternative hypotheses.Ho: bo = b1 = b= 0H: One or more of the parameters is not equal to zero.Ho: One or more of the parameters is not equal to zero.H3: b, = b2 = 0Ho: b1 = b2= 0H: One or more of the parameters is not equal to zero. (b) Use a = 0.01 to test for a significant relationship.State the null and alternative hypotheses.O Ho: bo = b1b2= 0H: One or more of the parameters is not equal to zero.Ho:: One or more of the parameters is not equal to zero.Hai b1 = b2= 0Ho: b1b2= 0H: One or more of the parameters is not equal to zero.Ho: One or more of the parameters is not equal to zero.Ha: bo = b1= 0Find 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-valueWhat is your conclusion?Reject Ho. We cannot conclude that the relationship is significant.Do not reject Ho. We conclude that the relationship is significant.Do not reject Ho. We cannot conclude that the relationship is significant.Reject Ho. We 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

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A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y = Bo + B,x + € 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. Vehicle Speed (x) Traffic Flow (y) 1,258 35 1,330 40 1,225 30 1,336 45 1,347 50 1,124 25 In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation. ŷ = bo + b;x + bx² (a) Develop an estimated regression equation for the data of the form ŷ = b, + b,x + b,x². (Round b, to the nearest integer and b, to two decimal places and b, to three decimal places.) (b) Use a = 0.01 to test for a significant relationship. State the null and alternative hypotheses. O Ho: bo = b, = b2 = 0 H: One or more of the parameters is not equal to zero. O Ho: One or more of the parameters is not equal to zero. Hại b, = b2 = 0 O Ho: b, = b2 = 0 H: One or more of the parameters is not equal to zero.

A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y = Bo + B,x + € 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. Vehicle Speed (x) Traffic Flow (y) 1,258 35 1,330 40 1,225 30 1,336 45 1,347 50 1,124 25 In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation. ŷ = bo + b;x + bx² (a) Develop an estimated regression equation for the data of the form ŷ = b, + b,x + b,x². (Round b, to the nearest integer and b, to two decimal places and b, to three decimal places.) (b) Use a = 0.01 to test for a significant relationship. State the null and alternative hypotheses. O Ho: bo = b, = b2 = 0 H: One or more of the parameters is not equal to zero. O Ho: One or more of the parameters is not equal to zero. Hại b, = b2 = 0 O Ho: b, = b2 = 0 H: One or more of the parameters is not equal to zero.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.5 8.2 6.9 3.3 2.8 2.2 2.6 0.6 yy 13.7 10.9 10.2 7 6.1 5.8 6.3 4.2 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.87x+3.9.y=0.87x+3.9. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 2.5 thousand automatic weapons?Answer =  Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 5.2 thousand automatic weapons?Answer =  Round to 3 decimal places. Submit QuestionQuestion 17
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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.6 8.5 7.2 3.6 2.6 2.3 2.1 0.4 yy 13.8 11.4 9.9 7.1 5.9 5.8 5.8 4.7 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.84x+4.02.y=0.84x+4.02. Use this equation to answer the following;Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 4.9 thousand automatic weapons?Answer =  Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 10.3 thousand automatic weapons?Answer =  Round to 3 decimal places.
A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized: y = B, + B,x + E 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 (y) Vehicle Speed (x) 1,257 35 1,329 40 1,227 30 1,335 45 1,351 50 1,123 25 In working further with this problem, statisticians suggested the use of the following curvilinear estimated regression equation. ý = bo + b,x + b,x? (a) Develop an estimated regression equation for the data of the form ý = b, + b,x + b,x2. (Round b, to the nearest integer and b, to two decimal places and b, to three decimal places.)
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