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Answer :
Final answer:
For standardizing a process, the desired normal curve would align with the 68-95-99.7 distribution, indicative of a 'skinny' distribution with a mean of 0 and standard deviation of 1.
Explanation:
When standardizing a process and referring to a normal curve, we would like to see the curve follow the 68-95-99.7 distribution, also known as the Empirical Rule. This rule indicates that for a normal distribution, approximately 68 percent of the data falls within one standard deviation of the mean, 95 percent within two standard deviations, and over 99 percent within three standard deviations.
A standard normal distribution is a special case where the mean (μ) is 0 and the standard deviation (σ) is 1, resulting in a 'skinny' curve that is highly standardized.
The options 'fat' and 'skinny' in the question informally refer to the spread of the data. A 'fat' distribution has a larger standard deviation, showing a wider spread of data, while a 'skinny' distribution is tighter with most data points close to the mean.
The term DMAIC refers to a data-driven improvement cycle used for optimizing and stabilizing business processes and designs, which is not a distribution but rather a methodology. Thus, the desired distribution for standardizing a process would be 'skinny,' following the standard normal distribution, i.e., 68-95-99.7 rule.
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