Foundations in Statistical Decision Making
Learn how to conduct experiments and analyze data to make better technical decisions in manufacturing. This intermediate-level statistical toolkit provides practical examples and case studies, covering topics such as hypothesis testing, T tests, Z tests, design and analysis of experiments, ANOVA, and Taguchi methods. Taught by manufacturing professionals, this course is designed for industrial engineers, quality engineers, process engineers, and manufacturing managers looking to enhance their decision-making skills. Sign up today to gain a clear understanding of statistical models and advance your career in manufacturing.
How to conduct experiments and analyze the resulting data to help make better technical decisions about equipment, processes and measurement systemsAn intermediate-level statistical tool kit aimed at the manufacturing professionalPractical examples and case studies from a manufacturing settingHypothesis Testing – What is it and How to apply it?T tests, Z tests – With examples in Microsoft ExcelDesign and Analysis of Experiments (DOE)DOE terminology and techniquesANOVA, One and Two Factor – Also with examples in Microsoft ExcelFull Factorial ExperimentsFractional Factorial ExperimentsTaguchi Experimental MethodsShow moreShow lessEffective decision making is what separates successful manufacturing professionals from everyone else. And to make effective technical decision, you must correctly understand, analyze and interpret the data.More than hazarding a guess or using simple tools like averages and visualizations, this class will teach you a broad selection of intermediate-level statistical tools useful in solving your difficult quality, engineering and process improvement problems.Topics in Foundations in Statistical Decision Making include:The benefits and advantages of statistical experimentsHypothesis testing – where and why it’s used.Error in hypothesis testingDesigning a statistical experimentT tests for meansZ tests for means and proportionsDesign and analysis of experiments (DOE)Practical tips for a successful DOEOne and two factor analysis of variance (ANOVA)Full factorial experimentsFractional factorial experimentsAn introduction to Taguchi MethodsA case study showing an L8 Taguchi experimentLots of real-life examples from manufacturingReferences for your further studyAnd MUCH moreUnlike some classes taught from a purely academic perspective with little connection to the real world, this class was designed and taught by manufacturing professionals for manufacturing professionals. By the time you are done with this course, you will have a clear understanding how to use statistical models in your work, and be prepared to continue your training onto to more advanced statistical tools.So if you’re a manufacturing, quality, process or industrial engineer or manager looking to take the next step in your decision making skills, this is the class for you!!Sign up today!!Who this course is for:Industrial engineers, Manufacturing engineersQuality engineers and quality techniciansProcess engineers and process techniciansManufacturing managers
User Reviews
Be the first to review “Foundations in Statistical Decision Making”
You must be logged in to post a review.


There are no reviews yet.