Statistical Thinking for Industrial Problem Solving, presented by JMP

Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems. Students completing this course will be able to:• Explain the importance of statistical thinking in solving problems • Describe the importance of data, and the steps needed to compile and prepare data for analysis • Compare core methods for summarizing, exploring and analyzing data, and describe when to apply these methods • Recognize the importance of statistically designed experiments in understanding cause and effect

• 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.

Syllabus

Syllabus - What you will learn from this course
Week 1
Course Overview
Module 1: Statistical Thinking and Problem Solving
In this module you learn about the course and about accessing JMP software in this course.
Week 2
Module 2A: Exploratory Data Analysis, Part 1
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.
Week 3
Module 2B: Exploratory Data Analysis, Part 2
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.
Week 4
Module 3: Quality Methods
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.
Week 5
Module 4: Decision Making with Data
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.
Week 6
Module 5: Correlation and Regression
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.
Week 7
Module 6: Design of Experiments (DOE)
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.
Week 8
Module 7: Predictive Modeling and Text Mining
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.
Week 9
Review Questions and Case Studies

FAQ

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Reviews

Really good course, learnt a tremendous amount.

Thanks

one of the best course for data discovery , nice example and flow of course

This course it's incredibly well structured, I relly enjoyed learning with it!

It is a really exhilarating course testing your practical and theoretical understanding about the subject covering most fields in the topic of data analytics along with jmp, a user-friendly platform.