How suggestions are chosen
The dashboard first applies your area, rating-span, and grades-served filters. Schools must also have the same school type. When only the starting school's rating span is selected, suggestions use the same rating span and number of scored measures. Selecting additional spans broadens the list across accountability formulas.
Rating span is the accountability classification used for state formula rules and letter-grade cut scores; grades served is the school's actual grade range. A school qualifies for the grade filter when it serves at least one checked grade.
Each selected similarity characteristic has equal influence. For each numeric characteristic, the dashboard measures the difference from the starting place and divides it by the typical variation—its standard deviation—among eligible places. Enrollment uses a logarithmic scale so relative size matters more than the raw student-count gap. Community setting is compared by the distance between city, suburb, town, and rural categories.
The standardized differences are averaged, then converted to match strength using
100 × e
−average standardized difference
, rounded to a whole percent. A 100% match is closest on the selected characteristics; the percentage falls as the differences grow. It is a similarity guide, not a rating or statistical probability.
For privacy, suppressed values such as N<10 are treated as unavailable and are never estimated. Overall scores, grades, and indicator results never influence the suggestions.
Community setting describes the area around a school, not the students who attend it. For a district, the dashboard shows the setting that accounts for the largest share of enrollment across its schools. Economically disadvantaged uses the public free/reduced-price lunch measure.