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EME 210: Data Analytics for Energy Systems

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Lessons

Orientation
Lesson 1: Getting Set Up and Started with Python
Lesson 2: Types of data and summarizing data
Lesson 3: Data visualization
Lesson 4: Confidence intervals and bootstrapping
Lesson 5: Hypothesis testing and randomization
Lesson 6: Normal distribution and Central Limit Theorem
Lesson 7: Chi-square Tests and ANOVA
Lesson 8: Linear regression
Lesson 9: Multiple Linear Regression
Lesson 10: Neural Networks
Lesson 11: Random Forests
Lesson 12: Probability

Author: John Smith, Lecturer, MGIS program, The Pennsylvania State University.

This courseware module is offered as part of the Repository of Open and Affordable Materials at Penn State.

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The John A. Dutton Institute for Teaching and Learning Excellence is the learning design unit of the College of Earth and Mineral Sciences at The Pennsylvania State University.

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