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Laura Lancaster
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Laura Lancaster is a statistical applications developer in the JMP Division of SAS Institute.

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Process Capability in JMP 12

In my previous blog post, I announced the new Process Capability platform in JMP 12 and shared some of the ideas that steered its development. Process capability analysis is used in many industries for assessing how well a stable process is performing relative to its specifications; it helps quality practitioners

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Coming in JMP 12: Process Capability

Process capability analysis is an essential part of Six Sigma and many other quality initiatives that are used in a wide variety of industries. It assesses how well a stable process is performing relative to its specifications and helps quality practitioners understand the current state of their process so they

2
New Multiple Comparisons options in JMP 11

In a study, analysts often need to compare treatment means to determine which treatments are better or worse and by how much. There are a variety of ways to compare treatment means. Some of the most common are all pairwise comparisons of treatment means, comparisons of all treatment means against

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Celebrating statisticians: Florence Nightingale

This month we have chosen Florence Nightingale as an influential statistician to celebrate for the International Year of Statistics. While Florence Nightingale is most well-known as the founder of modern nursing and worldwide healthcare reform, she was also a passionate statistician and a pioneer in statistical graphics. Florence Nightingale was born on

2
New Distribution options in JMP 10: Custom Quantiles

My previous blog post discussed two new options in the JMP 10 Distribution platform for customizing the summary statistics and default quantiles reports. This blog post discusses another new JMP 10 feature for the Distribution platform for continuous data: Custom Quantiles. This feature gives the user even more customization options for studying

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New Distribution customizations & options in JMP 10

The Distribution platform, frequently the backbone of data exploration, is one of the most widely used platforms in JMP. The JMP 10 Distribution platform has additional customizations and options to make this phase of data exploration even more individualized and easier than before. This blog post will focus on the reports