What’s next: The future of data literacy education
AI changes what we teach, not just how. Episode 5 looks at open questions — curriculum, assessment, equity — and where statistical education goes from here.
AI changes what we teach, not just how. Episode 5 looks at open questions — curriculum, assessment, equity — and where statistical education goes from here.
"The AI said so" — a student's answer to a completely misinterpreted regression. Episode 4 looks at the real risks of AI in the statistics classroom, and four practical guardrails that keep students thinking instead of just approving output.
What if students could ask their analysis question in plain English and get a real result in seconds? Episode 3 looks at JMP Assistant in practice — what it does well, and why the instructor's role just got more interesting, not smaller.
Students can produce statistical output faster than ever. Evaluating it is a different skill — and that's where the real teaching challenge lies. Episode 2 of my series on AI in the statistics classroom: what changes, what helps, and what's actually on the instructor.
Before AI enters the statistics classroom, what does a genuinely good teaching tool look like without it? Episode 1 of my new series makes the case for JMP Student Edition - a professional environment, not a simplified one.
Introduction Welcome to the finale of our space filling DOE series! After establishing our framework and evaluation methodology in the previous posts, we now present the comprehensive results of our comparative study. The findings provide clear guidance on when and how to select the most appropriate space filling design for your specific application. Summary of key findings Our analysis across f...
In JMP Live (and in JMP), it's possible for one local data filter to affect more than just one output in a window. Read on to learn how to use a data filter context box to make this happen.
Ron S. Kenett is awarded the Deming Medal and revisits the importance of information quality in this era of AI.
All a visualization really wants is to be useful.
The visualization step is critical to doing analytics because people are truly awful at reading tables of numbers. I'm sorry, but there it is. If the table has more than a few lines, you lose almost any hope of finding trends or data quality issues. I was recently reading a book on data science for Python – guess where they started? With tables, four chapters on tables, modeling, and summary stati...
Many people think the Distribution platform is a beginner tool or overly simplistic. That couldn't be further from the truth.
JMP is designed with a specific workflow in mind. Mastering this four-step workflow will help you to understand where to look in any JMP report for answers.
I recently received some requests to share information on using the REST-based Snowflake data connector with JMP 19. Luckily, I had already made a video about it! Easiest post ever.
The results of our 2025 JMP Wish List Prioritization Survey are in! Read on for more.
Discover how JMP Tech Support goes beyond problem-solving to help you learn, explore, and succeed with confidence in 2026.
“We have been raised on a steady diet of mixed messages regarding failure.”
Spectral analysis is a cornerstone of analytical chemistry, materials science, and countless other fields where understanding molecular signatures drives discovery. Yet one of the most persistent challenges analysts face is baseline drift – those unwanted variations in signal intensity that can mask true spectral features and compromise quantitative analysis. Today, we're excited to showcase how J...
JMP offers a world-class design of experiments (DOE) platform, which has been widely used by scientists and engineers across a diverse range of industries such as the pharmaceutical, semiconductor, and chemical industries. But would you be surprised if someone told you that JMP’s DOE platform can also be of aid in your artistic endeavors? Read more to find out how!