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A manufacturer of computer chips has a computer hardware company as its largest customer. The computer hardware company requires all of its chips to meet specifications of 1.2 cm. The vice-president of manufacturing, concerned about a possible loss of sales, assigns
his production manager the task of ensuring that chips are produced to meet the specification of 1.2 cm. Based on the production run from last month, a 95% confidence interval was computed for the mean length of a computer chip resulting in:
95% confidence interval: (0.9 cm, 1.1 cm)
The elements the production manager should consider in determining his company’s ability to produce chips that meet specifications includes what the confidence interval is, the population mean, and what the population standard deviation is. The production manager should consider these three actions because the “confidence intervals provide us with an upper
and lower limit around our sample mean, and within this interval we can then be confident we
have captured the population mean” (UserTesting, 2023), the population mean tells us the mean or average found in a population, and the population standard deviation tells us about the variability in the data.
From our data, a 95% confidence interval was calculated from 0.9 to 1.1 cm and this tells us that 95% of the samples collected fall within the 0.9 and 1.1 cm range and is the mean.
Although 0.9-1.1cm is the mean and range for what 95% of chips specifications fall within, there will be about 5% of outliers that do not fall within this range. This all tells us that the chips are not meeting the desired specifications of 1.2 cm.
To justify that the production team is not meeting specifications to the vice-president, the production manager should explain that the production team is not meeting specifications
