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Statistical Thinking for Industrial Problem Solving, presented by JMP

Mia Stephens

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

Read more

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

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What's inside

Syllabus

Course Overview
In this module you learn about the course and about accessing JMP software in this course.
Module 1: Statistical Thinking and Problem Solving
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Is highly relevant to data analytics professionals in STEM fields
Taught by JMP, who are recognized for their work in statistical software tools
Designed for scientists and engineers with intermediate knowledge of statistics

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Reviews summary

Practical statistical thinking with jmp for engineers

According to students, this course offers a highly practical and applicable approach to statistical problem-solving for engineers and scientists. Learners praise the instructor's clear explanations and the seamless integration of JMP software, which facilitates hands-on learning. Key modules like Quality Methods and Design of Experiments (DOE) are frequently highlighted for their direct relevance to industrial work. While the course excels in providing a solid foundation, some learners noted the fast pace of later modules and a heavy reliance on JMP, which might be a consideration for those preferring other statistical tools or seeking deeper theoretical dives.
Instructor effectively simplifies complex statistical concepts.
"The instructor explains complex statistical concepts in a very understandable way..."
"Fantastic course! The instructor's explanations are crystal clear..."
"The instructor's passion for the subject shines through. The instructor's explanations are solid."
JMP software is seamlessly integrated with practical demonstrations.
"The examples using JMP are highly practical... The JMP integration was seamless and very intuitive."
"The JMP software integration is a strong point, as it allows for hands-on learning without getting bogged down in coding."
"The JMP demos are really well done. It focuses on using JMP effectively for common problems."
Course content is directly applicable to real-world industrial problems.
"I found the modules on DOE and Quality Methods directly applicable to my work."
"I've already started applying some of the control chart principles at my workplace. The content is directly applicable..."
"I learned how to use practical tools and strategies that I could apply immediately to my work."
"The course delivers on its promise of practical statistical thinking. It's very useful for industrial applications."
Opportunity for more interactive exercises and dedicated projects.
"My main feedback would be for more interactive exercises or perhaps a dedicated project..."
"The case studies help, but more hands-on practice would be beneficial."
Course is heavily dependent on JMP, potentially limiting for others.
"The course content is solid, but it relies heavily on JMP. If you don't have access or prefer other software (like R or Python), it might be a hindrance."
"The reliance on JMP is also a bit limiting for general statistical practitioners."
"It's definitely targeted at a very specific audience (JMP users, industrial focus)."
Later modules can feel rushed, some desiring more theoretical depth.
"Some topics, like predictive modeling, felt a bit rushed given their complexity..."
"I found the pace in the later modules (DOE, Predictive Modeling) to be quite fast, which made it challenging to absorb everything..."
"I expected more depth in certain areas. While it gives a good overview, someone with prior statistical knowledge might find some parts too basic and others too rushed."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Statistical Thinking for Industrial Problem Solving, presented by JMP with these activities:
JMP Software Tutorial
Review the JMP software tutorial to familiarize yourself with the tools and features you'll use throughout the course.
Show steps
  • Go to the JMP website and navigate to the tutorials section.
  • Select the tutorial for your skill level and follow the instructions.
  • Complete the exercises and quizzes to test your understanding.
Review Probability and Statistics
Reviewing Probability and Statistics will provide a stronger understanding of the foundational concepts used throughout this course.
Browse courses on Probability
Show steps
  • Review notes from a previous course or textbook on Probability and Statistics.
  • Complete practice problems to test your understanding.
Statistical Thinking Workshop
Attend a statistical thinking workshop to gain practical experience in applying statistical methods to real-world problems.
Browse courses on Statistical Thinking
Show steps
  • Research statistical thinking workshops in your area.
  • Register for a workshop that aligns with your interests and skill level.
  • Attend the workshop and actively participate in the activities.
  • Apply the concepts learned in the workshop to your coursework.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice Data Exploration and Visualization with JMP
Practicing with JMP will let you familiarize yourself with the software and improve your data exploration and visualization skills, which are essential for this course.
Show steps
  • Install JMP software and complete the introductory tutorials.
  • Import a dataset and explore it using JMP's interactive visualizations.
  • Create graphs and charts to visualize the data and identify patterns.
Participate in Online Discussion Forums
Engaging in discussions with other students will expose you to different perspectives and help you to deepen your understanding of the course material.
Browse courses on Collaboration
Show steps
  • Join online discussion forums related to the course topics.
  • Read through the discussions and participate by asking questions, sharing insights, and responding to others.
Develop a Statistical Problem-Solving Plan
Creating a statistical problem-solving plan will help you to develop a structured approach to solving problems using statistical methods.
Browse courses on Statistical Thinking
Show steps
  • Identify the problem you want to solve.
  • Create a process map to visualize the steps involved in solving the problem.
  • Determine the data you need to collect and analyze.
  • Select the appropriate statistical methods to use.
Apply Statistical Methods to a Real-World Problem
Working on a real-world project will provide you with practical experience in applying statistical methods to solve problems.
Show steps
  • Identify a real-world problem that can be addressed using statistical methods.
  • Collect and analyze data relevant to the problem.
  • Develop and implement a statistical model to solve the problem.
  • Write a report summarizing your findings.
Develop a Data Visualization Dashboard
Creating a data visualization dashboard will enhance your ability to communicate data insights in a clear and impactful way.
Browse courses on Data Visualization
Show steps
  • Gather and prepare data relevant to the topic of your dashboard.
  • Select appropriate visualizations to represent the data effectively.
  • Develop an interactive dashboard using JMP or other visualization tools.
  • Share your dashboard with others and gather feedback.

Career center

Learners who complete Statistical Thinking for Industrial Problem Solving, presented by JMP will develop knowledge and skills that may be useful to these careers:
Quality Engineer
In a Quality Engineer role, you will apply statistical methods to improve the quality of products and processes. Statistical Thinking for Industrial Problem Solving will help you build a foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to identify and solve quality problems in a variety of industries.
See salaries and explore the career path for Quality Engineer
Data Analyst
Data Analysts use their statistical knowledge and skills to transform raw data into actionable insights. This course will provide you with a solid foundation in statistical analysis, data visualization, and data management. You will learn how to use these skills to extract insights from data and solve business problems.
See salaries and explore the career path for Data Analyst
Operations Research Analyst
Operations Research Analysts use statistical and mathematical techniques to improve the efficiency and effectiveness of operations. Statistical Thinking for Industrial Problem Solving will provide you with a strong foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to model and analyze operations, and to develop and implement solutions to improve performance.
See salaries and explore the career path for Operations Research Analyst
Market Research Analyst
Market Research Analysts use statistical methods to collect, analyze, and interpret data about markets and customers. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to design and conduct market research studies, and to analyze and interpret the results.
See salaries and explore the career path for Market Research Analyst
Business Analyst
Business Analysts use statistical methods to analyze business data and make recommendations for improvement. This course will help you develop the statistical skills and knowledge you need to succeed in this role. You will learn how to use statistical methods to identify trends, patterns, and relationships in data, and to make data-driven recommendations for improvement.
See salaries and explore the career path for Business Analyst
Financial Analyst
Financial Analysts use statistical methods to analyze financial data and make investment recommendations. Statistical Thinking for Industrial Problem Solving will provide you with a strong foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to analyze financial data, identify trends and patterns, and make informed investment decisions.
See salaries and explore the career path for Financial Analyst
Actuary
Actuaries use statistical methods to assess risk and uncertainty. Statistical Thinking for Industrial Problem Solving will provide you with a strong foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to assess risk and uncertainty, and to develop and implement solutions to mitigate risk.
See salaries and explore the career path for Actuary
Statistician
Statisticians use statistical methods to collect, analyze, and interpret data. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to design and conduct statistical studies, and to analyze and interpret the results.
See salaries and explore the career path for Statistician
Data Scientist
Data Scientists use statistical methods to extract insights from data. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to extract insights from data, and to develop and implement solutions to business problems.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers use statistical methods to develop and implement machine learning models. Statistical Thinking for Industrial Problem Solving will provide you with a strong foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to develop and implement machine learning models, and to evaluate their performance.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
Software Engineers use statistical methods to develop and test software. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to develop and test software, and to improve its quality and performance.
See salaries and explore the career path for Software Engineer
Industrial Engineer
Industrial Engineers use statistical methods to improve the efficiency and effectiveness of industrial processes. Statistical Thinking for Industrial Problem Solving will provide you with a strong foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to analyze and improve industrial processes, and to reduce costs and improve quality.
See salaries and explore the career path for Industrial Engineer
Manufacturing Engineer
Manufacturing Engineers use statistical methods to improve the efficiency and quality of manufacturing processes. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to analyze and improve manufacturing processes, and to reduce costs and improve quality.
See salaries and explore the career path for Manufacturing Engineer
Chemical Engineer
Chemical Engineers use statistical methods to design and optimize chemical processes. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to design and optimize chemical processes, and to reduce costs and improve quality.
See salaries and explore the career path for Chemical Engineer
Biomedical Engineer
Biomedical Engineers use statistical methods to design and test biomedical devices and systems. Statistical Thinking for Industrial Problem Solving will provide you with a solid foundation in statistical thinking, data analysis, and problem-solving. You will learn how to use these skills to design and test biomedical devices and systems, and to improve their safety and efficacy.
See salaries and explore the career path for Biomedical Engineer

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Statistical Thinking for Industrial Problem Solving, presented by JMP.
Cover image
Applied Statistics and Probability for Engineers
Save
Covers a wide range of statistical methods and applications for engineers. It comprehensive textbook that provides a solid foundation in statistical thinking and problem solving.
Applied Statistics and Probability for Engineers,...
Kindle Edition
$$$$
Applied Statistics and Probability for Engineers
Loose Leaf
$$$$
Applied Statistics and Probability for Engineers
Hardcover
$$$$
Applied Statistics and Probability for Engineers
Paperback
$$$
Applied Statistics and Probability for Engineers
Hardcover
$$$
Applied Statistics and Probability for Engineers,...
Paperback
$$$$
Applied Statistics And Probability for Engineers
Hardcover
$$$
Applied Statistics and Probability for Engineers,...
Loose Leaf
$$$$
Applied Statistics and Probability for Engineers
Hardcover
$$$$
Applied Statistics and Probability for Engineers,...
Loose Leaf
$$$$
Statistics for Engineers and Scientists
Save
Provides a solid foundation in statistical methods and applications for engineers and scientists. It covers a wide range of topics relevant to industrial problem solving, including data exploration, probability, statistical inference, and regression analysis.
Statistics for Engineers and Scientists
Paperback
Check
Statistics for Engineers and Scientists
Kindle Edition
Check
Cover image
Probability and Statistics for Engineers and...
Save
Provides a comprehensive introduction to probability and statistics for engineers and scientists. It covers a wide range of topics, including probability distributions, hypothesis testing, and regression analysis.
Probability & Statistics for Engineers & Scientists
Kindle Edition
$$$
Probability and Statistics for Engineers and...
Hardcover
$$$$
Probability & Statistics for Engineers & Scientists
Hardcover
$$$$
Probability & Statistics for Engineers & Scientists...
Paperback
$$$
Probability and Statistics for Engineers and...
Hardcover
$$$
Probability & Statistics for Engineers & Scientists...
Paperback
$$$
Cover image
Time Series Forecasting
Save
Covers the principles and applications of statistical quality control. It comprehensive textbook that provides a solid foundation in the use of statistical methods for improving quality.
Time Series Forecasting
Paperback
Check
Time Series Forecasting
Kindle Edition
Check
Cover image
Design Of Experiments
Save
Provides a comprehensive introduction to regression analysis for engineers and scientists. It covers a wide range of topics, including linear regression, multiple regression, and logistic regression.
Design Of Experiments
Paperback
Check
Design Of Experiments
Kindle Edition
Check
Cover image
Statistical Thinking
Save
Covers a wide range of statistical methods for engineering and quality assurance. It comprehensive textbook that provides a solid foundation in the use of statistical methods for solving problems in these fields.
Statistical Thinking: Improving Business...
Hardcover
$$$$
Statistical Thinking: Improving Business...
Kindle Edition
$$$$
Cover image
Practical Statistics for Data Scientists
Save
Provides a practical introduction to statistics for data scientists. It covers a wide range of topics, including data exploration, probability, statistical inference, and machine learning.
Practical Statistics for Data Scientists: 50+...
Paperback
$$
Practical Statistics for Data Scientists: 50...
Paperback
$$$
Practical Statistics for Data Scientists: 50+...
Hardcover
$$$$
Practical Statistics for Data Scientists: 50+...
Kindle Edition
$$
Introduction to Probability and Statistics for Data...
Save
Provides a comprehensive introduction to the design and analysis of experiments for engineers and scientists. It covers a wide range of topics, including experimental design, data analysis, and statistical inference.
Introduction to Probability and Statistics for Data...
Paperback
Check
Introduction to Probability and Statistics for Data...
Kindle Edition
Check
Cover image
The Six Sigma Handbook, Sixth Edition: A Complete...
Save
Focuses on the practical application of statistical methods for improving quality in industrial processes. It covers topics such as process mapping, control charts, and statistical tolerancing.
The Six Sigma Handbook, Sixth Edition: A Complete...
Hardcover
$$$
The Six Sigma Handbook, Sixth Edition: A Complete...
Kindle Edition
$$$
Cover image
PROBABILITY AND STATISTICS IN ENGINEERING, 4TH ED
Save
Provides a comprehensive introduction to statistical process control for engineers and scientists. It covers a wide range of topics, including control charts, process capability analysis, and gage repeatability and reproducibility.
PROBABILITY AND STATISTICS IN ENGINEERING 4/ED
Paperback
$$
Cover image
Design of Experiments for Engineers and Scientists
Save
Provides a comprehensive introduction to the design and analysis of experiments. It covers both classical and modern experimental designs, as well as topics such as response surface methodology and Taguchi methods.
Design of Experiments for Engineers and Scientists
Paperback
$$$
Design of Experiments for Engineers and Scientists
Paperback
$$$
Design of Experiments for Engineers and Scientists
Hardcover
$$$
Design of Experiments for Engineers and Scientists
Kindle Edition
$$$
Design of Experiments for Engineers and Scientists...
Kindle Edition
$$$
Design of Experiments for Engineers and Scientists
Kindle Edition
$$$
Cover image
Machine Learning Engineering
Save
Provides a comprehensive introduction to machine learning for engineers. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning.
Machine Learning Engineering
Paperback
$$
Machine Learning Engineering
Kindle Edition
$$

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Course image
Effort
8-week course, 3-6 hours per week
Level
Introductory
Via
Coursera
Institution
SAS
Instructor
Mia Stephens
Language
English
Transcripts
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Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Is highly relevant to data analytics professionals in STEM fields
Taught by JMP, who are recognized for their work in statistical software tools
Designed for scientists and engineers with intermediate knowledge of statistics
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