Mohammed Abdul Jawad

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Statistical Thinking for Industrial Problem Solving

Statistical Thinking for Industrial Problem Solvingjmp

Statistical Thinking
for Industrial Problem Solving

Learn more and enroll today.



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.


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:

  • Statistical Thinking and Problem SolvingStatistical 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 AnalysisLearn 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 MethodsLearn 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 DataLearn 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 RegressionLearn 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 ExperimentsIn 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.

Certification: Demonstrate your mastery by earning your certification in Statistical Thinking for Industrial Problem Solving. Learn more


Instructor Support Materials: Integrate STIPS content into your academic curriculum or commercial internal training using our customizable teaching materials. Request access.

Source: JMP 

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About JMP: JMP is a business unit of SAS that produces interactive software for desktop statistical discovery. Pronounced “jump,” its name suggests a leap in interactivity, a move in a new direction. John Sall, SAS co-founder and Executive Vice President, created this dynamic software and remains its chief architect and leader of the JMP division. Introduced in 1989 with scientists and engineers in mind, JMP has grown into a family of statistical discovery products used worldwide in almost every industry. From its beginnings, JMP software has empowered its users by enabling interactive analytics on the desktop.

JMP products continue to complement – and are often deployed with – SAS solutions that provide server-based business intelligence. The SAS commitment to accuracy, value and quality is evident in every JMP software release. Training, technical support, licensing and distribution are provided to JMP users the world over through SAS. Teams specializing in JMP products are located in the United States, Europe, China and Japan.

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