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A large box contains 10,000 ball bearings. A random sample of 120 is chosen. The sample mean diameter is 10 mm, and the standard deviation is 0.24 mm. True or false: a. A 95% confidence interval for the mean diameter of the 120 bearings in the sample is 10 ± (1.96)(0.24)/√ 120. b. A 95% confidence interval for the mean diameter of the 10,000 bearings in the box is 10 ± (1.96)(0.24)/√120. c. A 95% confidence interval for the mean diameter of the 10,000 bearings in the box is 10 ± (1.96)(0.24)/√10,000.

User Benji Lees
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1 Answer

4 votes

Answer:

Option a) A 95% confidence interval for the mean diameter of the 120 bearings in the sample is
10 \pm 1.96\displaystyle(0.24)/(√(120)).

Explanation:

We are given the following information in the question:

Sample size, n = 120

Sample mean = 10 mm

Standard Deviation = 0.24 mm

Formula:


\mu \pm z_(critical)(\sigma)/(√(n))


z_(critical)\text{ at}~\alpha_(0.05) = 1.96


10 \pm 1.96\displaystyle(0.24)/(√(120))

Hence, the correct interpretation for the confidence interval is given by option a).

A 95% confidence interval for the mean diameter of the 120 bearings in the sample is
10 \pm 1.96\displaystyle(0.24)/(√(120)).

We have to consider the factor of sampling of 120 ball bearings from a population of 10,000 ball bearings.

User Shane Sepac
by
5.1k points
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