To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 47 feet. Assume the population standard deviation is 4.2 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e). To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43feet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 47 feet. Assume the population standard deviation is 4.2 feet. At a = 0.10, can the engineer support the claim that the mean brakingdistances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).Click here to view page 1 of the standard normal distribution table.Click here to view page 2 of the standard normal distribution table.(a) Identify the claim and state Ho and Ha.What is the claim?O A. The mean braking distance is greater for Make A automobiles than Make B automobiles.O B. The mean braking distance is different for the two makes of automobiles.O C. The mean braking distance is less for Make A automobiles than Make B automobiles.O D. The mean braking distance is the same for the two makes of automobiles.What are Ho and H,?O A. Ho: H1SH2Ha: H1> H2O B. Ho: H1 H2Ha: H1 = H2O C. Ho: H1 H2Hai H1 SH2(b) Find the critical value(s) and identify the rejection region(s).The critical value(s) is/are(Round to three decimal places as needed. Use a comma to separate answers as needed.)What is/are the rejection region(s)?O A. z< -2.58O B. z< - 2.58, z> 2.58O C. z> 2.575O D. z< - 2.81O E. z< - 2.575, z> 2.575O F. z< - 1.645, z> 1.645O G. z< - 2.81, z> - 2.81H. z< - 1.96, z> 1.96(c) Find the standardized test statistic z for u1 - H2.(Round to three decimal places as needed.)(d) Decide whether to reject or fail to reject the null hypothesis. Choose the correct answer below.O A. Reject Ho. The standardized test statistic falls in the rejection region.B. Reject Ho. The standardized test statistic does not fall in the rejection region.O C. Fail to reject Ho. The standardized test statistic does not fall in the rejection region.O D. Fail to reject Ho. The standardized test statistic falls in the rejection region.(e) Interpret the decision in the context of the original claim.At the % significance level, there isevidence toV the claim that the mean braking distance for Make A automobiles isV the one for Make B automobiles.

Solution: Given information: n1= 35 Sample size make A n2= 35 Sample size make Bx1=43 feet Sample…

o compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is eet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 47 feet. Assume the population standard deviation is 4.2 feet. At a = 0.10, can the engineer support the claim that the mean braking istances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e). lick here to view page 1 of the standard normal distribution table. lick here to view page 2 of the standard normal distribution table. a) Identify the claim and state Ho and Ha Vhat is the claim? OA. The mean braking distance is greater for Make A automobiles than Make B automobiles. O B. The mean braking distance is different for the two makes of automobiles. OC. The mean braking distance is less for Make A automobiles than Make B automobiles. O D. The mean braking distance is the same for the two makes of automobiles. Vhat are Ho and H,? DA Ho: H1 SH2 Hại H1>H2 D D. Ho: H1 =42 O B. Ho: H1#H2 OC. Ho: H1 H2 Hai H1 SH2 P) Find the critical value(s) and identify the rejection region(s). he critical value(s) is/are. Round to three decimal places as needed. Use a comma to separate answers as needed.) What is/are the rejection region(s)? DA. z< -2.58 B. z< -2.58, z>2.58 DC. z>2.575 O D. z< -2.81 DE. z< -2.575, z>2.575 OF. z< -1.645, z> 1.645 O H. z< -1.96, z>1.96 O G. z< -2.81, z> - 2.81 E) Find the standardized test statistic z for u -H2. O (Round to three decimal places as needed.) d) Decide whether to reject or fail to reject the null hypothesis. Choose the correct answer below. DA. Reject Ho. The standardized test statistic falls in the rejection region.

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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To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 47 feet. Assume the population standard deviation is 4.2 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. Complete parts (a) through (e).

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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