Here’s your roadmap for the semester!
Content (): This page contains the readings, slides, and recorded lectures for the week. Read and watch these before our in-person class.
Example (): This page contains fully annotated R code and other supplementary information that you can use as a reference for your assignments and project. This is only a reference page—you don’t have to necessarily do anything here. Some sections also contain videos of me live coding the examples so you can see what it looks like to work with R in real time. This page will be very helpful as you work on your assignments.
Assignment (): This page contains the instructions for each assignment. Weekly reports are due by noon on the day of class. Other assignments are due by 11:59 PM on the day they’re listed.
You can subscribe to this calendar URL in Outlook, Google Calendar, or Apple Calendar:
Getting started
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Title
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Content
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Example
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Assignment
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Session 1
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August 22
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Introduction to the course
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Session 2
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August 24
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Basic data structures in R
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Session 3
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August 29
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Rmarkdown, pseudocode, and literate programming
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August 30
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Self-Evaluation 1 due (submit by 23:59:00)
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Session 4
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August 31
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Repetitive tasks, pipes, and functional programming
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Session 5
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September 5
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No Class
(Labor Day)
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Homework 1
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September 6
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Homework 1 (submit by 23:59:00)
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Spatial Data Operations in R
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Title
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Content
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Example
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Assignment
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Session 6
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September 7
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Spatial data is special data
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Session 7
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September 12
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Spatial data as vectors
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Session 8
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September 14
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Operations with vector data I
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Session 9
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September 19
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Operations with vector data II
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Session 10
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September 21
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Spatial data as matrices and rasters
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Session 11
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September 26
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Operations with raster data I
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Session 12
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September 28
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Operations with raster data II
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Session 13
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October 3
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Combining vector and raster operations (submit by 23:59:00)
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Homework 2
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October 4
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Homework 2 (submit by 23:59:00)
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Statistical Workflows for Spatial Data
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Title
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Content
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Example
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Assignment
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Session 14
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October 5
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Building analysis databates using attributes
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Session 15
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October 10
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Building analysis databates using location
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Session 16
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October 12
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Assessing spatial autocorrelation
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Session 17
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October 17
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Point pattern analysis and hypothesis testing
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October 18
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Self-Evaluation 2 due
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Session 18
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October 19
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Interpolation
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Session 19
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October 24
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Multivariate statistical analysis I
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Session 20
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October 26
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Multivariate statistical analysis II
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Session 21
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October 31
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Multivariate statistical analysis III
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Homework 3
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November 1
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Homework 3 (submit by 23:59:00)
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Visualizing Spatial Data
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Title
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Content
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Example
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Assignment
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Session 22
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November 2
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Basic data visualization principles
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Session 23
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November 7
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Introduction to ggplot
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Session 24
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November 9
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Maps, truth, and cartography
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Session 25
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November 14
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Static maps in R
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Session 26
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November 16
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Building better maps
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Homework 4
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November 18
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Homework 4 (submit by 23:59:00)
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Session 27
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November 21
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No Class
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Session 28
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November 23
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No Class
(Fall Break)
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Session 29
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November 28
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Introduction to interactive maps I
(Fall Break)
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Session 30
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November 30
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Interactive maps II
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Wrapup
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Title
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Content
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Example
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Assignment
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Final Project Draft
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December 2
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Final Project Draft (submit by 23:59:00)
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Session 31
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December 5
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Conclusion
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Session 32
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December 7
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Final Project Workday
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Final Project
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December 15
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Final Project Due (submit by 23:59:00)
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December 16
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Final Self-Evaluation Due (submit by 23:59:00)
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