Statistical Thinking Background

Statistical Thinking for Industrial Problem Solving (STIPS)

A free online statistics course

In virtually every field, deriving insights from data is central to problem solving, innovation and growth. But without an understanding of which approaches to use, and how to interpret and communicate results, the best opportunities will remain undiscovered.

That’s why we created Statistical Thinking for Industrial Problem Solving (STIPS). This online statistics course is available – for free – to anyone interested in building practical skills in using data to solve problems better.

Have two minutes? Learn more.

All you need is a browser, an internet connection and an inquisitive mind.

This course is comprised of seven modules, totaling about 30 hours of self-paced learning.  You can take one module or take them all. Each module includes short instructional videos, JMP demonstrations, questions and exercises. Review the full course outline page or PDF, or learn more about each module below:

All course content is now updated for JMP 17.

Statistical Thinking and Problem Solving

Statistical thinking is about understanding, controlling and reducing process variation. Learn about process maps, problem-solving tools for defining and scoping your project, and understanding the data you need to solve your problem.

Exploratory Data Analysis

Learn the basics of how to describe data with graphics and statistical summaries. Then, learn how to use interactive visualizations to communicate the story in your data. You'll also learn some core steps in preparing your data for analysis.

Quality Methods

Learn about tools for quantifying, controlling and reducing variation in your product, service or process. Topics include control charts, process capability and measurement systems analysis.

Decision Making With Data

Learn about tools used for drawing inferences from data. In this module you learn about statistical intervals and hypothesis tests. You also learn how to calculate sample size and see the relationship between sample size and power.

Correlation and Regression

Learn how to use scatterplots and correlation to study the linear association between pairs of variables. Then, learn how to fit, evaluate and interpret linear and logistic regression models.

Design of Experiments

In this introduction to statistically designed experiments (DOE), you learn the language of DOE, and see how to design, conduct and analyze an experiment in JMP.

Predictive Modeling and Text Mining

Learn how to identify possible relationships, build predictive models and derive value from free-form text.

Teach with STIPS

Integrate STIPS content into your academic curriculum or commercial internal training using our customizable teaching materials.

  • STIPS is excellent in balancing statistical theory and the practical hands-on use of JMP to solve common problems that many organizations deal with on a routine basis. Learn More
    Pete Cannon, NVIDIA
  • I’m getting feedback from my students that they really like STIPS. It’s multimedia, it’s lively, things are well explained and they can complete it at their own pace. Just last week, one student told me ‘I think I finally understand statistics.’ Learn More
    Phil Ramsey, University of New Hampshire
  • STIPS is a very good course. I was happy to have one online course concentrating a lot of important information in an easy, understandable level. Learn More
    Andreas Trautmann, Lonza
  • The instructional method is excellent...The lessons are short and tight. They have just the right amount of complex information broken down into manageable chunks.
    Award of Excellence, Society of Technical Communication