Master data-driven decision making through statistical analysis, sampling techniques, and risk assessment methods.
Master data-driven decision making through statistical analysis, sampling techniques, and risk assessment methods.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full The Data Driven Manager Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
What you'll learn
Plan and execute effective data acquisition strategies
Calculate and interpret effect size, power, and sample size
Perform best-case and worst-case scenario analyses
Conduct hypothesis testing for decision making
Use statistical estimation for risk reduction
Skills you'll gain
This course includes:
4 Hours PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course focuses on data acquisition and statistical analysis for business and engineering professionals. Students learn essential sampling techniques, estimation methods, and risk analysis tools using RStudio and ROIStat. The curriculum covers fundamental concepts of statistical inference, hypothesis testing, and effect size calculations, enabling learners to make data-driven decisions and minimize risk in capital investments.
Fundamentals of Sampling
Module 1 · 1 Hours to complete
Estimation
Module 2 · 1 Hours to complete
Best Case / Worst Case Analysis
Module 3 · 2 Hours to complete
Foundations of Hypothesis Testing
Module 4 · 1 Hours to complete
Essentials for Effect Size Calculations
Module 5 · 2 Hours to complete
Fee Structure
Instructor
W. Edwards Deming Professor of Management
Wendy Martin is the W. Edwards Deming Professor of Management in the Lockheed-Martin Engineering Management Program at the University of Colorado Boulder, where she specializes in Quality Science. With a robust educational background, she earned her B.S. in Mechanical Engineering from Purdue University and a Master of Engineering from the University of Colorado Boulder, focusing on Six Sigma, quality systems, and applied statistics. Before her academic career, Wendy honed her skills in statistical methods through training at Luftig & Warren International and gained extensive industry experience during her 14 years at Anheuser-Busch, where she applied statistical techniques in an industrial setting.Since joining the Engineering Management program in 2014, Professor Martin has taught a variety of courses related to data analytics and quality management, including "Data Acquisition, Risk, and Estimation" and "Stability and Capability in Quality Improvement." Her expertise encompasses operational excellence, product quality, and reliability methods. In addition to her teaching responsibilities, she consults with organizations to address critical process-related challenges. Outside of academia, Wendy enjoys exploring generative AI and workflow automation, reflecting her commitment to continuous learning and innovation in both her professional and personal pursuits.
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