Applied ML Systems · Capstone brief
DS-02 · Is the property assessment fair across the county?
Assessment regressivity — where lower-value homes are assessed at a higher fraction of market value than higher-value homes — is measurable. Is it present here?
The question
Henrico publishes assessed values and sale prices. Assessment regressivity — where lower-value homes are assessed at a higher fraction of market value than higher-value homes — is measurable. Is it present here?
Data
Henrico County open GIS and real estate assessment data (https://data-henrico.opendata.arcgis.com/). Census ACS tract-level income and demographics (https://www.census.gov/data/developers/data-sets/acs-5year.html).
Expected failure modes
Sale price is not market value — foreclosures, family transfers, and teardowns pollute the ratio. Assessment year and sale date must be aligned or the ratio is meaningless. Small tracts produce wild ratios from three sales. The standard statistics here (price-related differential, coefficient of dispersion) have established definitions the student should use rather than invent.
Done looks like
A sales-ratio study using recognized measures, with arm's-length filtering documented, tract-level results mapped, and a clear statement of where the sample was too thin to conclude anything.
Five C's
CT: distinguishing a real pattern from small-sample noise. CR: building a defensible arm's-length filter from messy transaction records. CO: having a peer re-run the filter independently and comparing counts. CM: a two-page finding a non-technical reader could bring to a public meeting. CZ: this is a tax-fairness question about real neighbors — the standard of evidence is correspondingly high.
Mentor role
An assessor, appraiser, real-estate analyst, or municipal finance staffer reviews the filtering logic at Checkpoint 1 and the conclusions at Checkpoint 2. School-supervised.
Rubric calibration
R1: asks a ratio question, not a "are assessments accurate" question. R2: every exclusion rule is written down and counted. R3: uses standard ratio statistics correctly. R4: reports confidence, and refuses thin tracts. R5: readable by a homeowner. R6: states plainly what the study cannot establish about intent.
Two ways this goes wrong
(a) The student divides assessment by sale price for every record, finds "regressivity," and has actually found foreclosures. (b) The student concludes the county is discriminating, on 40 sales, with no uncertainty interval — an overclaim that would not survive one question from a county analyst.
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