Answered: A manufacturer of electronic kits has…

Name: A manufacturer of electronic kits has found that the mean time require
Uploaded: 2024-03-20T07:07:12.000Z
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Description: A manufacturer of electronic kits has found that the mean time required for novices to assemble its new circuit tester is 3 hours, with a standard deviation of 0.20 hours. A consultant has developed a new instructional booklet intended to reduce the

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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A manufacturer of electronic kits has found that the mean time required for novices to assemble its new circuit tester is 3 hours, with a standard deviation of 0.20 hours. A consultant has developed a new instructional booklet intended to reduce the time an inexperienced kit builder will need to assemble the device. In a test of the effectiveness of the new booklet, 15 novices require a mean of 2.90 hous to complete the job. Assuming the population of times is normally distributed, and using the 0.05 level of significance, should we conclude that the new booklet is effective?

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The test statistics is -1.53 and is more than critical value, so new booklet is effective

The test statistics is -1.73 and is more than critical value, so new booklet is not effective

The test statistics is -2.14 and is less than critical value, so new booklet is not effective

The test statistics is -1.94 and is less than critical value, so new booklet is effective

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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