What are the opening hours?

Monday 8:30am - 4:30pm Tuesday 8:30am - 4:30pm Wednesday 8:30am - 4:30pm Thursday 8:30am - 4:30pm Friday 8:30am - 4:30pm

Stat-Ease, Inc.

Name: Stat-Ease, Inc.
Address: Minneapolis, MN, US
Telephone: +16123789449

Design-Expert and Stat-Ease 360 software can help you improve your bottom line. Training available! Learn how to make the most of your experiments.

www.statease.com - go to Learn DOE for resources.

04/13/2026

When you're running a designed experiment, you're rarely optimizing for just one thing. But how does Stat-Ease software actually find the "sweet spot" when your responses are competing with each other?

In her blog post, Stat-Ease consultant Shari Kraber walks you through the numerical optimization algorithm behind Stat-Ease software: how desirability is calculated, how goals and limits shape the search, and how the algorithm finds conditions that work for all your responses at once.

If you've ever wondered what's happening under the hood when you hit "optimize," this one's worth a read.

04/09/2026

Better experiments don't happen by accident. They happen when you know the right tools and how to use them.

Our upcoming workshop lineup covers the full range of DOE skills: from getting started with factorial designs, to optimizing processes with RSM, to mastering mixture designs for formulation work. All courses are instructor-led, online, and designed to get you results fast.

Sign up today - link is in the comments!

04/07/2026

When you're optimizing a product or process, you're rarely chasing just one goal. It can feel overwhelming to juggle multiple responses, competing priorities, and tricky tradeoffs. So let Stat-Ease software do it for you!

In this webinar from 2020, Stat-Ease consultant Shari Kraber peels back the curtains on the powerful optimization tools in Stat-Ease software, showing you how to set goals, adjust relative importance, and find the most desirable "sweet spot" even when your responses are pulling in different directions.

Watch the recording on our YouTube channel today!

04/02/2026

The latest edition of Mark Anderson's DOE FAQ Alert is out! 🔬

This edition tackles a question we hear surprisingly often: is it OK to ignore some of your data to increase R-squared? As someone who's seen this mistake made more times than he can count, Mark has a lot to say about it.

Beyond the FAQ, each edition is packed with upcoming Stat-Ease training and events, curated blog recommendations, and a wry quote to send you off. Just six times a year, and it's all signal, no noise.

Not subscribed yet? Sign up at statease.com/publications/signup

03/30/2026

It's been a while, but here's another !

Sam Hickman joined our team in 2025 after starting his career with Little Free Library, and we're so glad to have him! Sam's work spans direct sales, financial analysis, compliance, and helping with client communications. He loves "finding the story in the numbers" and translating that into smarter business strategies, while at the same time working directly with customers at the intersection of data and cutting-edge software. Sam enjoys learning something new everyday from people who are genuinely world-class at what they do, and is excited to push towards new horizons for both Stat-Ease and our clients.

Thanks for what you do, Sam! 🎉

03/27/2026

🔬 If you're a formulator, make sure you're modelling your system correctly: with mixture designs.

Do you know if you need mixture designs? You need them when your responses are a function of the proportions of your components — and if you try to analyze a mixture as a factorial or RSM design, your model will be incorrect, wasting time and money.

Head over to our Instagram for the full tip, and if you want to go deeper, we have two upcoming training options: Fundamentals of Mixture DOE and Mixture Design for Optimal Formulations!

03/25/2026

If you're a formulator and still reaching for RSM by default, this post's worth a read.

Most design of experiments practitioners (even experienced ones) gravitate toward familiar factorial or RSM designs for everything. But formulations need mixture designs, and force-fitting the wrong tools onto your formulation can create real issues that are easy to miss.

In his latest post, Richard Williams breaks down what makes mixture designs unique, the problems you create when you avoid them, and why common workarounds like ratio-based RSM and slack variable approaches fall short.

Read it now on the Stat-Ease blog!

03/24/2026

We've been sharing lots of information about mixture designs for formulators this month. Here's another great resource: our YouTube channel.

We post recordings of all our informative, accessible DOE webinars for posterity, sorted into topical playlists and organized for easy access to our most popular videos. Our "Mixture Design for Formulators" playlist includes Martin Bezener's comprehensive overviews, software tutorials, and real-world examples from our Online DOE Summits.

Whether you're just starting with DOE or well on your journey, our YouTube channel has everything you need to make the most from your experiments: free, on demand, and ready when you are.

🔔 Subscribe and ring the bell so you never miss a new video!

03/19/2026

Still testing your formulation separate from its process? You could be missing out. 🔬

When you test them separately, you risk missing critical interactions between the two, like a recipe that performs best at a specific temperature or processing time. Combined designs in Stat-Ease software let you test mixture components and process factors together, so those interactions don't slip through the cracks. Fewer runs, yet richer insights. That's statistics made easy.

Download a free trial and see for yourself!

03/17/2026

🔬 This month's Feature Focus: KCV Models in Stat-Ease 360 and Design-Expert!

Combined mixture-process designs can require hundreds of runs as your experiment grows. KCV models strike a balance: fewer runs, without losing insight into how your mixture and process affect each other.

Head over to our Instagram for the full post! (Link in comments)

03/11/2026

Mixture models look nothing like the polynomial equations you learned in school: no intercept, no squared terms, and deceptively tricky coefficients. But if you're a formulator, mastering them should be your priority.

Let Mark Anderson break it down for you in his latest blog post, using the melting point of copper-gold blends as a concrete example. He covers how mixture models are structured, how to interpret their coefficients, and when to stop trying to interpret them and just let the model graphics do the talking.

Check it out! (see the comments for a link) 👇

Address

Minneapolis, MN

Opening Hours

Monday	8:30am - 4:30pm
Tuesday	8:30am - 4:30pm
Wednesday	8:30am - 4:30pm
Thursday	8:30am - 4:30pm
Friday	8:30am - 4:30pm

Telephone

+16123789449

Website

http://www.statease.com/

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