Statistical Thinking for Industrial Problem Solving, presented by JMP
Learn statistical thinking and problem-solving techniques in this applied statistics course for scientists and engineers. Gain the skills to analyze and solve real-world problems using data and basic statistical methods. Explore modules on data analysis, exploratory data analysis, quality methods, and more. Enhance your understanding of statistical concepts and their application in industrial problem-solving. Enroll now and unlock the power of statistical thinking for effective problem-solving.
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 you will learn
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.
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