Research surface·Denver tract data

Correlations

Cross-signal workspace for finding where housing, retail, safety, schools, and subsidy data reinforce each other or break the expected pattern.

Correlation lenses
9
Core two-axis relationships tracked in the lab.
Exception lenses
6
Mismatch screens for outliers worth validating.
Tracked areas
0
Denver tracts with valid data on both sides of the relationship.
Browse lenses

Scan the lab by the kind of relationship you are actually testing.

Grouped for fast operator scanning: housing and price pressure, retail and development change, then civic context.

Housing + Price

Price pressure, reinvestment, and housing-system signals that change how a tract reads on the map.

Retail + Development

Commercial change, development momentum, and storefront structure where visible neighborhood change first shows up.

Civic Context

Schools, subsidy concentration, and service footprint lenses for analysts who need context beyond price and retail.

Exception lenses

Mismatch screens for the places that break the easy story.

These stay secondary on purpose. Use them when you want the weird cases, then validate them against the full place context.

How to read this lab

Use correlations to frame the question, not to end the analysis.

Good use of this page looks like a workflow: spot the relationship, validate the place, then read the source notes before making a claim.

Correlation is a starting point

Use these lenses to spot reinforcement, mismatch, and outlier tracts. Do not treat any pair as a causal claim.

Validate with place pages

Once a relationship looks real, jump into the map, tract pages, and neighborhood pages to check the local shape of the signal.

Always read the source caveats

Retail, rent, subsidy, and safety signals arrive from different systems with different lag, coverage, and confidence.