How Science Turns Data Into Knowledge teaches you how to evaluate scientific claims critically, address experimental limitations, and recognize the roles of trust and responsibility within research.

How Science Turns Data Into Knowledge
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How Science Turns Data Into Knowledge
This course is part of Understanding Data: Navigating Statistics, Science, and AI Specialization

Instructor: Elle O'Brien
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What you'll learn
Learn the rationale and limitations of significance testing within scientific inquiry, including crafting hypotheses and interpreting p-values
Learn how scientific experiments are proposed, designed, reviewed, and published
Identify common biases and mistranslations in science research reporting and the challenges of conveying science research to the public effectively
Assess the credibility of claims about research and recognize the role of replicability and generalizability in scientific progress
Skills you'll gain
- Probability & Statistics
- Data Analysis
- Media and Communications
- Statistical Inference
- Peer Review
- General Science and Research
- Experimentation
- Statistical Hypothesis Testing
- Data Literacy
- Research
- Research Design
- Scientific Methods
- Science and Research
- Research Methodologies
- Analytical Skills
- Journalism
- Statistical Reporting
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There are 4 modules in this course
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University of Michigan

Madecraft

Johns Hopkins University
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