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.

Answer:Option a) A 95% confidence interval for the mean diameter of the 120 bearings in the sample is [tex]10 \pm 1.96\displaystyle\frac{0.24}{\sqrt{120}}[/tex].Step-by-step explanation:We are given the following information in the question:Sample size, n = 120Sample mean = 10 mmStandard Deviation = 0.24 mmFormula: [tex]\mu \pm z_{critical}\frac{\sigma}{\sqrt{n}}[/tex][tex]z_{critical}\text{ at}~\alpha_{0.05} = 1.96[/tex][tex]10 \pm 1.96\displaystyle\frac{0.24}{\sqrt{120}}[/tex]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 [tex]10 \pm 1.96\displaystyle\frac{0.24}{\sqrt{120}}[/tex].We have to consider the factor of sampling of 120 ball bearings from a population of 10,000 ball bearings.