Statistical Thinking for Industrial Problem Solving, presented by JMP from Coursera

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

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

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.

Module 2A: Exploratory Data Analysis, Part 1

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.

Module 2B: Exploratory Data Analysis, Part 2

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.

Module 3: 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.

Module 4: 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.

Module 5: 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.

Module 6: Design of Experiments (DOE)

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.

Module 7: Predictive Modeling and Text Mining

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

Review Questions and Case Studies

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

Good to know

Know what's good

, what to watch for

, 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

Reviews summary

Well-received statistical thinking course

Learners say this well-received course is engaging. According to students, the course provides a solid understanding of statistical thinking through its hands-on exercises and real-world examples that help learners apply skills to industrial problems. Reviewers praise the practicality of the course and its relevance to industry work.

Provides a clear foundation in statistical thinking.

"I gained a solid understanding of the fundamental concepts of statistical thinking."

Engaging content with hands-on exercises and real-world examples.

"The course was filled with hands-on exercises and real-world examples that allowed me to apply my newly acquired skills to industrial problems."

Highly relevant to industry work and practical applications.

"This course add great value in performing six sigma"

"The learning could e employed on any statistical software for ex: Python, R, Graphpad, Minitab, SPSS Etc."

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

Show steps

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

Show steps

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

Show steps

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

Show steps

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

Show steps

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

Show steps

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

Show steps

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

Show steps

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