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LAB 2 — ASSIGNMENT

Classification & Spatial Scale

Download the assignment file, complete the three questions, and submit your .qmd and rendered .html to Canvas.

Assignment Workflow

This file is identical to the tutorial
The pre-filled code (Steps 1–6) produces the same output as the tutorial. If this file is in the same folder as your tutorial QMD, you can knit immediately and see the same results. If you placed it in a different location, run the packages chunk first, then knit.
Need a Census API key?
Setup instructions are in the Lab 2 Tutorial under “Before You Begin.” Register free at api.census.gov/data/key_signup.html — key arrives by email within minutes.
1

Download and rename

Use the download link below. Save to your PAF516/Lab2/ folder. Rename to Lab2_Assignment_YourLastName.qmd before editing.

2

Knit the file first

Press Cmd+Shift+K (Mac) or Ctrl+Shift+K (PC). Steps 1–6 render automatically. Review the output — these are the results you will interpret for Q1.

3

Answer the three questions

Q1: Interpret the pre-filled results (text, 3 parts). Q2: Create a second bivariate map by filling in the scaffold chunks at the end of the file (code). Q3: Compare the two bivariate maps (text). Re-knit after completing Q2.

4

Submit to Canvas

Submit both Lab2_Assignment_YourLastName.qmd and Lab2_Assignment_YourLastName.html.

The Three Questions

Q1 Interpret: MAUP, Classification, and the Spatial Story Text answer — no code required

After knitting, answer the following three parts:

  • 1a. Zoom into Maricopa County in the interactive US county map (Step 6). Note the single hardship score for the entire county, then compare with the block group map in Step 4. Would a state official relying only on the county-level map get an accurate picture of where hardship is concentrated? Explain how the Modifiable Areal Unit Problem (MAUP) applies here and what it means for social policy decisions.
  • 1b. Look at the 2×2 classification comparison from Step 2. Which method makes hardship appear most widespread? Which makes it appear most concentrated?
  • 1c. In a policy memo arguing for increased funding to “high hardship” areas, which classification method would you choose and why? What about a memo arguing hardship is not widespread?

Replace the placeholder text in the Q1 section. A few sentences per bullet is sufficient.

Q2 Modify: Bivariate Map with Hardship x % Renter Code + output required

Create a second bivariate choropleth using hardship_index and pct_renter (percent renter-occupied housing) instead of pct_minority:

  • Use the same biscale workflow from Step 3
  • Two scaffold chunks are provided: q2.a (classify) and q2.b (map + legend)
  • Follow the same pattern: bi_class() → bi_scale_fill() → bi_legend() + inset_element()
Q3 Interpret: Comparing the Two Bivariate Maps Text answer — no code required

Compare the bivariate map from Step 3 (hardship × % minority) with your new map from Q2 (hardship × % renter):

  • Do the same areas show “double disadvantage” in both maps? Or do the spatial patterns differ?
  • What does this comparison tell you about the relationship between economic hardship, race/ethnicity, and housing tenure in Maricopa County?

Quick Reference

ActionMacPC
Run current chunkCmd+ReturnCtrl+Enter
Knit / RenderCmd+Shift+KCtrl+Shift+K

Download & Submit

Lab 2 Assignment File

Download Lab2_Assignment.qmd

Right-click → Save Link As. Save to your PAF516/Lab2/ folder.

Submit to Canvas

  • Lab2_Assignment_YourLastName.qmd — your edited source file
  • Lab2_Assignment_YourLastName.html — the rendered output
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