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EME 210
Data Analytics for Energy Systems

Geography Department Penn State

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Lesson 4: Confidence intervals and bootstrapping

Overview
Sampling Distributions
Standard Deviation and Standard Error
Introduction to For Loops
Bootstrapping
Bootstrapped Sampling Distributions
Introduction to Confidence Intervals
Confidence Intervals: The Percentile Method
Confidence Intervals: The Standard Error Method
Summary and Final Tasks
Lesson 4 FAQ

‹ Lesson 3 FAQ up Overview ›

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.

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