How to Describe Data
This course is part of Understanding Data: Stats, Science, and AI Explained.
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 Understanding Data: Navigating Statistics, Science, and AI 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
Evaluate the usefulness and reliability of statistical information
Understand uncertainty's role in measurements and data collection
Interpret and assess data visualizations effectively
Develop critical thinking skills for analyzing statistical claims
Identify potentially misleading statistics
Apply statistical literacy to everyday situations
Skills you'll gain
This course includes:
3.3 Hours PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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Get a Completion Certificate
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There are 4 modules in this course
This foundational course explores the fundamentals of data interpretation and statistical literacy. Students learn how to evaluate and interpret data in everyday contexts, understand uncertainty in measurements, and critically assess statistical claims. The curriculum covers essential topics including data summarization, visualization interpretation, and the evaluation of statistical reliability. Through practical examples and real-world applications, learners develop skills to identify misleading statistics and better understand data-driven claims encountered in daily life.
Welcome, Introduction & What Makes a Statistic Useful?
Module 1 · 2 Hours to complete
Rethinking Certainty
Module 2 · 2 Hours to complete
Talking about Numbers
Module 3 · 1 Hours to complete
Statistics, Skepticism and Trust
Module 4 · 2 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Understanding Data: Stats, Science, and AI Explained
Instructor
Lecturer IV & Research Investigator
Elle O'Brien is a lecturer and research investigator at the University of Michigan. She completed her MS in neuroscience and PhD in hearing science at the University of Washington. Elle spent a year working at an open-source software startup training data professionals to adopt principles from software engineering to make their analyses more reproducible. Now as a researcher and lecturer at the University of Michigan School of Information, Elle designs and teaches graduate courses about statistics and data science. She is also running a research program to study how scientists adopt new software, analysis methods, and technology.
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Frequently asked questions
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