Tag: Data Visualization

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Digging into my diet and fitness data

If you’re a regular reader of the JMP Blog, then you already know that those of us who work for JMP have taken a page from the Hair Club for Men. From our hobbies to internal activities, the people who work at JMP are also JMP users! I seriously considered

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Exploring data on the best pizza in the US

I am of Italian descent from the greater New York City area, so it should be no surprise that I love pizza. My interest was piqued when my niece Samantha recently posted a ranking of the “101 Best Pizzas in America," according to the Daily Meal® website, which conducted the

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The eggciting results of my designed eggsperiment

In my previous blog entry, I talked about my frustrations in making good-looking hard-boiled eggs that were easy to peel. My Internet searches found a number of different techniques that cooks said were essential to success, but I wanted to know which techniques were best. So I set up a

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Scagnostics JMP Add-In: A new way to explore your data

Scagnostics, scatterplot diagnostics, was discovered by John and Paul Tukey and later popularized by Leland Wilkinson in Graph-Theoretic Scagnostics (2005). These analyses were redefined in High-Dimensional Visual Analytics: Interactive Exploration Guided by Pairwise Views of Point Distributions (2006). The beauty of scagnostics is the ability to visually explore a data

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Fun and effective: Teaching statistics with JMP

JMP has a growing fan club of people who are passionate about the software as a great teaching tool to more easily convey statistical concepts. Colleagues on our global academic team and I pooled some comments from noteworthy educators about why they like teaching with JMP.   “In the early

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See optimal settings with JMP Pareto Efficient Frontier

Pareto Efficient Frontier (PEF) is becoming an increasingly popular tool for measuring and selecting project or design parameters that will yield the highest value at the lowest risk. PEF is being used widely in many industrial areas, such as when selecting the best exploration projects in oil and gas, finding

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