John Sall
John Sall RSS
Co-Founder and Executive Vice President, SAS

John Sall leads the JMP business unit at SAS and remains the chief architect of JMP statistical discovery software. JMP has been a part of SAS since the first version of JMP was launched in 1989, bringing interactive data visualization and analysis to the desktop.

Recent Posts

Cleaning categories at scale with Recode in JMP 12

Data entered manually is usually not clean and consistent. Even when data is entered by multiple-choice fields rather than by text-entry fields, it might need ... Read More

Flow and Frontier in JMP 12

Long lists of improvements go into each new version of our software, and usually there are one or two themes that characterize the release. JMP ... Read More

Statistical discovery with JMP at the 25-year point

For you, today is Oct. 4. At JMP, we call it Sept. 34. We had been determined to release the first version of JMP by ... Read More

“The desktop computer is dead” and other myths

The desktop or laptop is now in decline, squeezed from one side by mobile platforms and from the other side by the cloud. As a ... Read More

Big real data is different from big simulated data: Benchmarking

To benchmark computer performance on statistical methods with big data, we can just generate random data and measure performance on that, right? Well, it could ... Read More

It’s not just what you say, but what you don’t say: Informative missing values

Sometimes emptiness is meaningful. If a loan applicant leaves his debt and salary fields empty, don’t you think that emptiness is meaningful? If a job ... Read More

Big Data always has significant differences but not always practical differences: Practical significance and equivalence

When you have millions of observations of real data and do a simple fit across two variables, if you don’t get a significant test, then ... Read More

Bad data happens to good people: Robust to outliers

In semiconductor data, it is common for probe measurements that encounter an electrical short to exhibit measurements that are far out in the distribution, i.e., ... Read More

Not just filtering coincidences: False discovery rate

Purely random data has a 5% chance of being significant. Choose the most significant p-values from many tests of random data, and you will filter ... Read More

Violating Anna Karenina Principle: LogWorth scaling

The first line of Leo Tolstoy’s classic novel, Anna Karenina, begins: “Happy families are all alike; every unhappy family is unhappy in its own ... Read More