MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 - 9. Understanding Experimental Data

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What you'll learn

This course includes

12 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

6-0002-introduction-to-computational-thinking-and-data-science-fall-2016 arrays coefficient of determination computation data models hooke's law linear regression mean squared error polls polyfit spring constant variance

Full Transcript

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: http://ocw.mit.edu/6-0002F16 Instructor: Eric Grimson Prof. Grimson talks about how to model experimental data in a way that gives a sense of the underlying mechanism and to predict behavior in new settings. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

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