Lab 1 Tutorial | PAF 516

What You Will Build

In this lab you will construct a composite Economic Hardship Index from five US Census variables, evaluate its reliability using Cronbach's alpha, and map the results at three geographic scales — US counties (national), Arizona census tracts (state), and Maricopa County block groups (neighborhood).

The tutorial walks through every step with fully working code. Knit it first to see the finished product, then go back and run chunk by chunk to understand how it works.

Learning Objectives

Retrieve Census variables using tidycensus::get_acs()
Compute derived rates (poverty rate, unemployment rate, etc.) from numerator/denominator pairs
Standardize variables to z-scores and build a composite index
Assess internal consistency using psych::alpha()
Map the index at three geographic scales using ggplot2 + patchwork

Before You Begin

1 — File and Folder Setup

Create this folder structure before downloading anything. Move the downloaded .qmd into PAF516/Lab1/ before opening it in RStudio.

PAF516/
  Lab1/
    Lab1_Tutorial.qmd            ← downloaded tutorial (do not edit)
    Lab1_Tutorial.html           ← auto-generated when you knit
    Lab1_Assignment_Howell.qmd   ← your renamed assignment copy
    Lab1_Assignment_Howell.html  ← submit this to Canvas
  Lab2/  Lab3/  ...

2 — Install System Build Tools (Windows/Mac — Run Once)

⚠ One-time setup for the entire course

R needs a system-level compiler to install certain packages used in this course. You only need to do this once — it applies to all future labs.

Windows: Run these two lines in your RStudio Console:

install.packages("installr")
installr::install.Rtools()

Mac: Run this line in your Terminal (Applications → Utilities → Terminal):

xcode-select --install

Once complete, restart RStudio before proceeding.

3 — Install Packages (Run Once)

⚠ Do this before knitting

Open Lab1_Tutorial.qmd in RStudio
Click inside the packages chunk (labeled #| label: packages)
Press Cmd+Return (Mac) or Ctrl+Enter (PC) to run just that chunk
Wait — first run downloads and installs packages and may take 5–10 minutes
After it finishes, future knits will be fast — the renv block only runs once automatically

What is renv?

renv records the exact version of every package used so that code that works today still works next semester.

4 — Census API Key

The lab pulls live data from the Census Bureau. If you don't have a key yet:

Register free at api.census.gov/data/key_signup.html
Check email for your key (arrives within a few minutes)
In the RStudio console run: census_api_key("YOUR_KEY_HERE", install = TRUE)
Restart R: Session → Restart R

Running the Tutorial

Option A — Knit First (Recommended)

Click the Render button (blue arrow, top of editor) or press Cmd+Shift+K / Ctrl+Shift+K. This produces Lab1_Tutorial.html with all results — maps, tables, and the correlation matrix. Review the output to see what the completed analysis looks like.

Option B — Run Chunk by Chunk (Best for Learning)

Place your cursor inside any code chunk and press the run shortcut. Output appears inline. Fix any errors before moving on. This is how you understand what each step does.

Action	Mac	PC
Run current chunk	`Cmd+Return`	`Ctrl+Enter`
Run all chunks above	`Cmd+Option+P`	`Ctrl+Alt+P`
Knit / Render	`Cmd+Shift+K`	`Ctrl+Shift+K`

What's Inside

Step	What It Does
Step 1	Retrieve Census variables with `get_acs()` — Arizona census tracts
Step 2	Reshape to wide format and compute poverty, unemployment, education, and insurance rates
Step 3	Run `psych::alpha()` — assess reliability of the 5-item index
Step 4	Build the composite index (z-score row mean) and visualize its distribution
Step 5	Pull county-level data for the entire US and map national hardship patterns
Step 6	Map the index across Arizona census tracts
Step 7	Pull Maricopa County block groups and map neighborhood-level variation
Step 8	Combine all three maps side-by-side using `patchwork`

Download

Lab 1 Tutorial File

⬇ Download Lab1_Tutorial.qmd

Right-click → Save Link As. Save directly to your PAF516/Lab1/ folder. Do not open in the browser.