Week 7 videos

From overlay to regression lecture

• Overview (1:37 min)

Overlay analysis

• Layers in GIS (2:28 min)
• Overlay: GIS’s ‘killer app’ (5:53 min)
• Two approaches: vector and raster (4:37 min)
• Some points to note (5:38 min)

Combining layers different ways

• Black and white (2:31 min)
• Shades of grey (1:54 min)
• Weighted overlay (3:35 min)

From overlay to regression

• More evidence-based overlay (3:54 min)
• Weights-of-evidence overlay (5:42 min)
• How regression and overlay are related (3:39 min)

Regression lecture

Introduction

• Reminder of what regression is and its relation to overlay (7:47 min)

Simple example

The R script for this section is available here.

• Introducing a simple example (3:05 min)
• Building a simple model (4:40 min)
• Getting information about the model (3:32 min)
• Making the model a bit more complicated, and reflections (4:50 min)

A more complex model (Galapagos biodiversity)

The RMarkdown and data files for this example are available here (in a .zip archive, which you will need to unzip.)

• Introducing the data (4:22 min)
• The kitchen sink and other models (5:39 min)
• Mapping residuals (3:06 min)
• Stepwise search of models (5:44 min)

Wrap up

• Closing comments (4:26 min)

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Regression lecture supplemental materials

• A script to do the lapse rate example (you will need to install some packages to make this work)
• Materials for the Galapagos regression model example

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Various ways of using R (from 2020)

• Introduction and R scripts (12:17 min)
• R script comments (1:38 min)
• Markdown markup (8:28 min)
• Rmarkdown (8:47 min)
• Knitting Rmarkdown (5:42 min)
• Concluding remarks (2:53 min)