A&S500/Lin517 - Quantitative Investigations in the Social Sciences

This is the course website for Lin517/A&S500: Quantitative Investigations in the Social Sciences, taught in the Spring semester of 2023. Notes from in-class will be listed below.

Making a Quarto Site

The first thing to do is to set up a github repository with your quarto project in it. You can do this 1 of two ways:

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Quarto Finesse

Giving Quarto some polish

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Survey Responses

Source: ottlex.org

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Classifying documents, `quanteda`

While tidytext is part of the larger “tidytext” universe, there is also another -verse of packages for analyzing text in R, the quanteda-verse.

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Important Words

Words to just exclude from the analysis.

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Sentiment and Other Content Analyses

Length of each chapter in lines

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More Text

{tidytext}’s tokenizers don’t operate between rows…

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Starting with Text

String operations are going to be things like “split a string into substrings”

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Thematic Maps

Seems to have a number of defaults set to be more pleasant for maps.

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Raster data

Digital elevation model from https://kyfromabove.ky.gov/, specifically the tile that includes POT.

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Getting Data

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Spatial Operations

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Starting with Maps

sf seems to be the most tightly integrated package into the tidyverse workflow we’ve been using.

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Strings

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Census Data

In order to load this data, you’ll have to download it yourself from the Lexington data hub.

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Separating and Joining

The actual paper on the topic is worth reading: Wickham (2014). There are three rules to tidy data:

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Recoding and Joining

More working with babynames

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Dataframing

There are alot of interesting datasets out there that we could make plots with, but not without some pre-processing.

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ggplot2 extensions

There are a lot of ggplot2 extensions. You can browse some of them here:

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ggplot2 theming

We can configure the size of figures and other aspects of their appearance in a quarto document by setting certain quarto chunk options.

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Text and Labels

(not “criticism”)

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Continuing ggplot2

This packages lets us grab

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Starting ggplot2

in-class

Block 2

ggplot2

data-viz

The plots here look different from what we actually got in class because of settings I’ve set up at the website level!

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Data Viz notes

Block 2

data-viz

Here’s a classic example called Anscomb’s quartet.

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Navigating the R Ecosystem

Onboarding

This is a flowchart of my most frequent workflow for finding information about an R package.

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Basics of R Syntax

R basics

To run R code in a Quarto notebook, you need to insert a “code chunk”. In visual editor mode, you can do that by typing the forward slash (/) and start typing in “R Code Chunk”. In the source…

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Github Onboarding with RStudio

Block 1

Onboarding

Instruction boxes with should be done on github, and instruction boxes with should be done in RStudio.

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Plan for Onboarding Day

Block 1

Onboarding

General RStudio Project Creation

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Welcome Day

Block 1

Onboarding

Today, we talked about R vs RStudio Vs Quarto, which I illustrated like so:

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