SAS
Statistical Thinking for Industrial Problem Solving, presented by JMP

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SAS

Statistical Thinking for Industrial Problem Solving, presented by JMP

Mia Stephens

Instructor: Mia Stephens

10,192 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.9

(88 reviews)

Beginner level

Recommended experience

Flexible schedule
Approx. 44 hours
Learn at your own pace
96%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.9

(88 reviews)

Beginner level

Recommended experience

Flexible schedule
Approx. 44 hours
Learn at your own pace
96%
Most learners liked this course

What you'll learn

  • How to describe data with statistical summaries, and how to explore your data using advanced visualizations.

  • Understand statistical intervals, hypothesis tests and how to calculate sample size.

  • How to fit, evaluate and interpret linear and logistic regression models.

  • How to build predictive models and conduct a statistically designed experiment.

Details to know

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Assessments

229 assignments

Taught in English

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There are 10 modules in this course

In this module you learn about the course and about accessing JMP software in this course.

What's included

3 videos4 readings1 app item

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.

What's included

26 videos3 readings16 assignments1 app item7 plugins

Learn the basics of how to describe data with basic graphics and statistical summaries, and how to explore your data using more advanced visualizations. You’ll also learn some core concepts in probability, which form the foundation of many methods you learn throughout this course.

What's included

50 videos31 assignments1 app item4 plugins

Learn how to use interactive visualizations to effectively communicate the story in your data. You'll also learn how to save and share your results, and how to prepare your data for analysis.

What's included

36 videos2 readings31 assignments2 app items2 plugins

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.

What's included

41 videos3 readings26 assignments2 app items2 plugins

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.

What's included

47 videos2 readings38 assignments2 app items5 plugins

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.

What's included

43 videos2 readings30 assignments2 app items5 plugins

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.

What's included

36 videos2 readings25 assignments2 app items4 plugins

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

What's included

39 videos2 readings30 assignments2 app items

In this module you have an opportunity to test your understanding of what you have learned.

What's included

2 assignments1 app item

Instructor

Instructor ratings
4.8 (36 ratings)
Mia Stephens
SAS
1 Course10,192 learners

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SAS

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4.9

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