Master data analysis fundamentals with R software, from descriptive statistics to probability distributions. Perfect for beginners in data science.
Master data analysis fundamentals with R software, from descriptive statistics to probability distributions. Perfect for beginners in data science.
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 Data Science Methods for Quality Improvement 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.
4.6
(30 ratings)
4,603 already enrolled
Instructors:
English
What you'll learn
Calculate descriptive statistics using R software
Create effective graphical representations of data
Apply probability distributions to solve problems
Understand sampling and sampling distributions
Perform statistical inference and hypothesis testing
Classify different types of data using measurement scales
Skills you'll gain
This course includes:
5.5 Hours PreRecorded video
11 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course introduces learners to fundamental data analysis concepts and practical applications using R software. The curriculum covers data classification, descriptive statistics, probability distributions, and sampling methods. Through hands-on exercises, students learn to create graphical representations, calculate statistical measures, and perform basic inferential analyses. The course emphasizes practical skills while building a strong theoretical foundation in statistical concepts.
Data and Measurement
Module 1 · 2 Hours to complete
Describing Data Graphically and Numerically
Module 2 · 4 Hours to complete
Probability and Probability Distributions
Module 3 · 3 Hours to complete
Sampling Distributions, Error and Estimation
Module 4 · 3 Hours to complete
Two Sample Hypothesis Testing
Module 5 · 3 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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4.6 course rating
30 ratings
Frequently asked questions
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