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 41 feet. Assume the population standard deviation is 4.6 feet.The mean braking distance for Make B is 42 feet. Assume the population standard deviation is 4.4 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). (a) Identify the claim and state Ho and Ha. What is the claim? A.The mean braking distance is different for the two makes of automobiles. This is the correct answer. B.The mean braking distance is the same for the two makes of automobiles. C.The mean braking distance is less for Make A automobiles than Make B automobiles. Your answer is not correct. D.The mean braking distance is greater for Make A automobiles than Make B automobiles. Part 2 What are H0 and Ha? Part 3 (b) Find the critical value(s) and identify the rejection region(s). The critical value(s) is/are __ (Round to two decimal places as needed. Use a comma to separate answers as needed.) Part 4 What is/are the rejection region(s)? _ Part 5 (c) Find the standardized test statistic z for μ1−μ2. z=_ (Round to two decimal places as needed.) Part 6 (d) Decide whether to reject or fail to reject the null hypothesis. Part 7 (e) Interpret the decision in the context of the original claim. At the_% significance level, there is (insufficient/ suffcient) evidence to (support/ reject) the claim that the mean braking distance for Make A automobiles is (different from /greater than / less than /equal to) the one for Make B automobiles.

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter7: Analytic Trigonometry

Section7.6: The Inverse Trigonometric Functions

Problem 91E

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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

41 feet. Assume the population standard deviation is 4.6 feet.The mean braking distance for Make B is

42 feet. Assume the population standard deviation is 4.4 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).

(a) Identify the claim and state Ho and Ha.

What is the claim?

A.The mean braking distance is different for the two makes of automobiles.

This is the correct answer.

B.The mean braking distance is the same for the two makes of automobiles.

C.The mean braking distance is less for Make A automobiles than Make B automobiles.

Your answer is not correct.

D.The mean braking distance is greater for Make A automobiles than Make B automobiles.

Part 2

What are H0 and Ha?

Part 3

(b) Find the critical value(s) and identify the rejection region(s).

The critical value(s) is/are ______

(Round to two decimal places as needed. Use a comma to separate answers as needed.)

Part 4

What is/are the rejection region(s)?

_______

Part 5

z=_____

(Round to two decimal places as needed.)

Part 6

(d) Decide whether to reject or fail to reject the null hypothesis.

Part 7

(e) Interpret the decision in the context of the original claim.

At the___% significance level, there is (insufficient/ suffcient) evidence to (support/ reject) the claim that the mean braking distance for Make A automobiles is (different from /greater than / less than /equal to) the one for Make B automobiles.

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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