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Description: a construction company is developing a machine to make bricks. A sample of 90 bricks made by the machine were weighed with sample mean 5.6 lbs, where ”lbs” is pounds. Assume that the weight of bricks has a distribution with standard deviation σ = 0.5

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 construction company is developing a machine to make bricks. A sample of 90 bricks made by the machine were weighed with sample mean 5.6 lbs, where ”lbs” is pounds. Assume that the weight of bricks has a distribution with standard deviation σ = 0.5 lbs.

(i) Find the 95% confidence interval for the true mean weight of bricks made by the machine.

(ii) To satisfy building standards, bricks must have error in weight of ±0.05 lbs from the mean weight. At 95% confidence level, what is the minimum number of bricks which must be weighed to make sure that the machine is making bricks satisfying building standards?

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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