placestats

Infant mortality and Average test score

Across 1,103 counties, Infant mortality and Average test score have a link of -0.56, 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 -0.24 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

Infant mortality

Deaths of babies before their first birthday per 1,000 babies born alive.

County Health Rankings · County Health Rankings v129

Average test score

How far above or below the national average children here score on tests, in grade levels. Minus one means about a year behind. It reflects everything in children's lives, not only their schools.

Stanford Education Data Archive · SEDA cs_mn_avg_ol

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 infant mortality

Infant mortalityAverage test score
Highest
Kusilvak Census Area, AK20.2-1.31
Oglala Lakota County, SD16.9-1.12
Todd County, SD15.4-1.21
Big Horn County, MT15.3-0.861
Cheboygan County, MI14.6-0.151
Lowest
Marin County, CA1.570.329
San Francisco County, CA2.65-0.0706
Placer County, CA2.710.166
Rockingham County, NH2.740.413
Sherburne County, MN2.760.281

By average test score

Infant mortalityAverage test score
Highest
Forsyth County, GA3.950.713
Norfolk County, MA2.80.652
Morris County, NJ2.870.627
Williamson County, TN3.020.621
Hamilton County, IN4.90.619
Lowest
Kusilvak Census Area, AK20.2-1.31
Bethel Census Area, AK8.62-1.27
Todd County, SD15.4-1.21
Oglala Lakota County, SD16.9-1.12
Jasper County, SC8.53-0.868
States — Average test score is not published for states

By infant mortality

Infant mortalityAverage test score
Highest
Mississippi8.7—
Arkansas7.78—
Louisiana7.53—
Alabama7.49—
West Virginia7.09—
Lowest
Massachusetts3.72—
New Hampshire3.82—
New Jersey3.98—
Vermont4.08—
California4.12—
Metro areas

By infant mortality

Infant mortalityAverage test score
Highest
Forrest City, AR13.3-0.774
Greenville, MS13.1-0.59
Minden, LA12.9-0.456
Natchitoches, LA12.2-0.428
Kinston, NC12-0.23
Lowest
Santa Fe, NM2.8-0.335
Rexburg, ID2.960.112
San Jose-Sunnyvale-Santa Clara, CA3.010.175
Bend, OR3.110.000491
Santa Rosa-Petaluma, CA3.14-0.164

By average test score

Infant mortalityAverage test score
Highest
Celina, OH5.180.473
Boulder, CO3.250.45
Boston-Cambridge-Newton, MA-NH3.30.42
State College, PA5.160.412
Fort Collins-Loveland, CO3.740.406
Lowest
Forrest City, AR13.3-0.774
Shawano, WI8.86-0.756
Clarksdale, MS10.2-0.69
Clearlake, CA5.34-0.613
Orangeburg, SC11.4-0.61

Counties furthest from the pattern

Compared with the straight line that best fits all 1,104 counties: the five with far more average test score than their infant mortality would suggest, and the five with far less.

Infant mortalityAverage test score
Above the line
Orange County, NC7.630.537
Forsyth County, GA3.950.713
Hamilton County, IN4.90.619
Ozaukee County, WI5.330.569
Jay County, IN9.780.261
Below the line
Bethel Census Area, AK8.62-1.27
Jasper County, SC8.53-0.868
Lake County, CA5.34-0.613
Imperial County, CA3.56-0.472
Monterey County, CA4.7-0.534

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-0.5561,103 counties reporting both
After adjusting for density, income and education-0.241the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.298size taken out as well as density
Also comparing only within each state-0.331each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight-0.137the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 216 equally weighted counties
Middle value inside single states-0.605the link worked out inside each of 23 states with at least 20 counties reporting
Using ranks, after adjusting-0.125uses 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 = 5.0e-16. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 0.002. 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 1.4e-15.

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 +0.47 (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 Infant mortality and Average test score