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EME 210
Data Analytics for Energy Systems

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Lesson 1: Getting Set Up and Started with Python

Overview
What are data?
Why Python?
Understanding Python
Getting Started with Python and Google Colab
Getting Help
Python Coding Fundamentals: Libraries
Data Structures
Data Structures: Pandas
Importing Files: Option 1
Importing Files: Option 2
Importing Files: Option 3
Dictionaries vs. DataFrames
Summary and Final Tasks
Lesson 1 FAQ

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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

Authors: Eugene Morgan, Associate Teaching Professor and Renee Obringer, Assistant Teaching Professor, Energy Mineral Engineering, The Pennsylvania State University.

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

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