Data Driven Decision Making
Master statistical analysis techniques for business and engineering decisions using RStudio and ROIStat.
Master statistical analysis techniques for business and engineering decisions using RStudio and ROIStat.
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:
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What you'll learn
Perform statistical tests for data comparison
Analyze relationships between variables
Conduct two-sample tests for independent data
Implement dependent data analysis methods
Master Analysis of Variance techniques
Skills you'll gain
This course includes:
5.9 Hours PreRecorded video
5 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course focuses on statistical analysis for data-driven decision making in business and engineering contexts. Students learn to perform various statistical tests including one-sample tests, correlation analysis, two-sample tests for both independent and dependent data, and Analysis of Variance (ANOVA). The curriculum emphasizes practical application using RStudio and ROIStat software, enabling students to analyze real-world data and make informed decisions based on statistical evidence.
One Sample Tests
Module 1 · 2 Hours to complete
Correlation and Association
Module 2 · 2 Hours to complete
Two Sample Tests for Independent Data
Module 3 · 2 Hours to complete
Two Sample Tests for Dependent Data
Module 4 · 2 Hours to complete
The One Way Analysis of Variance
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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