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distribution

Resource Page: A Primer on Non-normal Data

The distribution of data can be categorized in two ways: normal and non-normal. If data is normally distributed, it can be expected to follow a certain pattern in which the data tend to be around a central value with no bias left or right (Figure 1). Non-normal data, on the other hand, does not tend…

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Getting the Most out of a Capability Analysis

The process capability indices Pp and Cp describe how closely a process can operate within its specification limits. Many articles describe the difference between Pp and Cp simply: one is short term, one is long term. Moving beyond such a description, this article focuses on the untapped power of capability analysis and shows you how…

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Better Project Management Through Beta Distribution

As a Six Sigma professional responsible for managing projects, have you ever been asked the following questions? When do you reasonably expect to complete your project? What’s the probability of completing the project on time or on a given date? Which activities on the critical path should you focus your attention on to meet the…

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Piggybacking Air Filters to Save Shipping Costs

Cummins operates three plants San Luis Potosi, Mexico, which produce and ship products daily to distribution centers in the United States. These plants produce systems such as reconditioned engines, alternators, and filtration and exhaust systems. Two of the three plants were looking for ways to reduce the high costs of trucking the products, so Rebecca…

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Tips for Recognizing and Transforming Non-normal Data

Six Sigma professionals should be familiar with normally distributed processes: the characteristic bell-shaped curve that is symmetrical about the mean, with tails approaching plus and minus infinity (Figure 1). When data fits a normal distribution, practitioners can make statements about the population using common analytical techniques, including control charts and capability indices (such as sigma…

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Estimation Method Aids in Analyzing Truncated Data Sets

When working with data sets, practitioners sometimes encounter metrics, such as out-of-roundness and loss-of-moisture measurements, with physical limits. In these scenarios, the data distribution is truncated at the value of physical limitation, creating a distribution outside of the criteria of a normally distributed population. With non-normal data, estimates and predictions using the normal distribution are…