Here’s your roadmap for the semester!
Content (): This page contains the readings, slides, and recorded lectures for the week. Read the various readings before our scheduled class time.
Lesson (): This page contains a tutorial video and additional annotated R code and other supplementary information that you can use to help you prepare for the in-class exercises and assignments. These are most helpful if you watch them before in-class sessions so that you can ask questions when we start working through things together.
Exercises (): This page the scripts that we work on in class as a reminder of some of the live-coding exercises. These are provided as a reference to help you link your notes to the syntax we use in class.
Assignment (): This page contains the instructions for each assignment. Assignments are due by 11:59 PM on the day they’re listed. One more time!
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Getting Started
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Title
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Content
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Lesson
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Exercises
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Assignment
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August 25
(Session 1)
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Introduction to the Course
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August 27
(Session 2)
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Tools of the Trade
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August 29
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Self-Evaluation 1 due (submit by 11:59 PM)
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September 1
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No Class
(Labor Day)
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September 3
(Session 4)
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Meeting Your data
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September 8
(Session 5)
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Data Manipulation with the tidyverse
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September 10
(Session 6)
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Pipes, Functions, and Iteration
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September 26
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Homework 1
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Fundamentals of Spatial Data
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Title
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Content
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Lesson
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Exercises
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Assignment
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September 15
(Session 7)
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Data Models, Coordinates, and Geometries
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September 17
(Session 8)
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Projections, Extent, and Resolution
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September 22
(Session 9)
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Attribute Data Operations
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September 24
(Session 10)
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Spatial Data Operations
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September 29
(Session 11)
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Geometry Data Operations and Troubleshooting
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October 1
(Session 12)
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Building Spatial Databases
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October 1
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Final Project Contract Due
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October 2
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Homework 2
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Describing Spatial Patterns
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Title
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Content
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Lesson
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Exercises
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Assignment
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October 6
(Session 13)
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Building Spatial Databases II
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October 8
(Session 14)
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Workday
(no inclass session)
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October 13
(Session 15)
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Point Patterns I
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October 15
(Session 16)
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Point Patterns II
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October 20
(Session 17)
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Surface Metrics
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October 22
(Session 18)
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Multivariate Description
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October 23
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Homework 3
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Explaining Spatial Patterns
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Title
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Content
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Lesson
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Exercises
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Assignment
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October 27
(Session 19)
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Interpolation
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October 29
(Session 20)
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Kriging
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November 1
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Homework 1 Revision
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November 1
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Homework 2 Revision
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November 1
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Final Project Description Due
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November 3
(Session 21)
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Machine Learning Models I
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November 5
(Session 22)
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Machine Learning Models II
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November 10
(Session 23)
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Statistical Modelling I
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November 12
(Session 24)
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Statistical Modelling II
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November 12
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Homework 3 Revision
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November 17
(Session 25)
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Spatial Autocorrelation I
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November 19
(Session 26)
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Spatial Autocorrelation II
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November 20
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Homework 4
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Fall Break
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Title
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Content
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Lesson
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Exercises
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Assignment
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November 24
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No Class
(Fall Break)
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November 26
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No Class
(Fall Break)
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Predicting Spatial Patterns
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Title
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Content
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Lesson
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Exercises
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Assignment
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December 1
(Session 29)
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Spatial Predictions
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December 2
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Homework 4 Revision
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December 3
(Session 30)
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Prediction and Model Evaluation I
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December 8
(Session 31)
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Model Evaluation II
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Wrapup
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Title
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Content
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Lesson
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Exercises
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Assignment
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December 8
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Draft Final Project Due (submit by 11:59 PM)
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December 10
(Session 32)
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Conclusion
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December 18
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Final Project Due (submit by 11:59 PM)
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December 19
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Final Self-Evaluation Due (submit by 11:59 PM)
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