placestats

Homicide rate and Economic connectedness in high school

Across 1,124 counties, Homicide rate and Economic connectedness in high school have a link of -0.52, on a scale from −1 (opposite) to +1 (in step). But compare places with the same population density, income and education, and a weak link of -0.20 remains. Most of the first figure came from both measures following how urban, rich and educated a place is, not from a link with each other.

Mostly gone after adjusting

Every place, plotted

One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.

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What each measure is

Homicide rate

Deaths recorded as homicide per 100,000 people. It comes from death certificates, not police reports.

County Health Rankings · County Health Rankings v015

Economic connectedness in high school

How many of a low-income teenager's high school friends are high-income, compared with an even mix. It is counted in the county of the school, not where the person lives as an adult, so it describes where people grew up.

Social Capital Atlas · Opportunity Insights child_ec_county

Highest and lowest

Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.

Counties

By homicide rate

Homicide rateEconomic connectedness in high school
Highest
Phillips County, AR57.40.491
St. Louis city, MO50.60.808
Leflore County, MS48.40.433
Washington County, MS46.90.477
Lowndes County, AL460.459
Lowest
Morris County, NJ0.6581.42
Rockingham County, NH0.8271.23
Davis County, UT0.9221.37
Delaware County, OH0.9511.21
York County, ME0.9581.03

By economic connectedness in high school

Homicide rateEconomic connectedness in high school
Highest
Howard County, MD3.151.56
Loudoun County, VA1.071.55
Stafford County, VA3.161.53
St. Mary's County, MD3.391.5
Prince William County, VA3.31.48
Lowest
Holmes County, MS44.30.273
McDowell County, WV190.282
Clay County, KY9.940.302
Floyd County, KY80.308
Wilcox County, AL39.50.348
States — Economic connectedness in high school is not published for states

By homicide rate

Homicide rateEconomic connectedness in high school
Highest
District of Columbia23—
Mississippi16—
Louisiana15.9—
Alabama12.7—
Missouri11—
Lowest
New Hampshire1.52—
Maine1.59—
Vermont2.04—
Idaho2.19—
Rhode Island2.29—
Metro areas

By homicide rate

Homicide rateEconomic connectedness in high school
Highest
Greenville, MS46.90.477
Selma, AL41.50.564
Greenwood, MS40.90.453
Pine Bluff, AR37.30.64
Clarksdale, MS33.10.362
Lowest
Portland-South Portland, ME1.071.06
Provo-Orem-Lehi, UT1.221.38
State College, PA1.241.08
Iowa City, IA1.411.14
Barnstable Town, MA1.441.05

By economic connectedness in high school

Homicide rateEconomic connectedness in high school
Highest
Lexington Park, MD3.391.54
Fairbanks-College, AK10.41.38
Provo-Orem-Lehi, UT1.221.38
Urban Honolulu, HI2.711.35
Minot, ND3.531.34
Lowest
Pikeville, KY5.940.338
Deming, NM9.920.35
Clarksdale, MS33.10.362
Corbin, KY8.340.362
Forrest City, AR26.70.409

Counties furthest from the pattern

Compared with the straight line that best fits all 1,124 counties: the five with far more economic connectedness in high school than their homicide rate would suggest, and the five with far less.

Homicide rateEconomic connectedness in high school
Above the line
St. Louis city, MO50.60.808
Howard County, MD3.151.56
Charles County, MD8.121.45
Stafford County, VA3.161.53
Loudoun County, VA1.071.55
Below the line
Pike County, KY4.670.359
Floyd County, KY80.308
Clay County, KY9.940.302
Logan County, WV7.520.349
Fayette County, WV6.450.371

Two series, one county

Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.

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Every version of the link

Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.

Before adjusting for anything-0.5201,124 counties reporting both
After adjusting for density, income and education-0.203the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.193size taken out as well as density
Also comparing only within each state-0.184each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.160the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 219 equally weighted counties
Middle value inside single states-0.528the link worked out inside each of 22 states with at least 20 counties reporting
Using ranks, after adjusting-0.117uses each county’s rank, not its value, so a few extreme counties cannot create the link

How much to believe it

Could it be chance?

The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 7.2e-12. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.001. The site tested 20,910 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 1.8e-11.

Do nearby places look alike?

Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.34 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.

Did they change together?

Not measurable: at least one of these is published for too few of the years a change needs (2014–2019 or 2019–2023), or for too few counties in both.

Related pairs

Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Homicide rate and Economic connectedness in high school