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Data source: US Social Security Administration
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Popularity of the first name Leeann correlates with...

VariableCorrelationYearsSys. Score
Arson in United Statesr=0.9738yrs437
Burglary rates in the USr=0.9738yrs437
Remaining Forest Cover in the Brazilian Amazonr=0.9836yrs435
Burglaries in Floridar=0.9838yrs418
The divorce rate in Kentuckyr=0.9723yrs416
The divorce rate in North Carolinar=0.9723yrs416
Milk consumptionr=0.9732yrs412
Google searches for 'desktop background'r=0.9516yrs406
United States music album salesr=0.9516yrs404
Gasoline pumped in Francer=0.9543yrs400
Kerosene used in Thailandr=0.9442yrs398
Kerosene used in Argentinar=0.9342yrs396
The number of recreational therapists in Connecticutr=0.9720yrs392
The number of computer programmers in Michiganr=0.9620yrs392
The number of data entry keyers in Minnesotar=0.9720yrs392
US average milk-fat content of milk fat and skim solids byproduct fluid beverage milkr=0.9622yrs389
Portion of all US dairy skim-solids allocated to the production of fluid beverage milkr=0.9522yrs388
Arson in New Jerseyr=0.9738yrs387
US birth rates of triplets or morer=0.9520yrs386
The distance between Neptune and the Sunr=0.9348yrs385
The distance between Neptune and Earthr=0.9348yrs385
The distance between Neptune and the moonr=0.9348yrs385
The divorce rate in Mississippir=0.9523yrs383
Physical album shipment volume in the United Statesr=0.9424yrs381
Cigarette Smoking Rate for US adultsr=0.9521yrs380
The wind speed in Austinr=0.9439yrs378
Burglaries in Illinoisr=0.9738yrs377
GMO use in corn grown in Texasr=0.9618yrs374
Google searches for 'oprah winfrey'r=0.919yrs372
Pirate attacks globallyr=0.9114yrs371
US music album salesr=0.9116yrs368
Viewership count for Days of Our Livesr=0.8747yrs368
Burglaries in Marylandr=0.9738yrs367
Air pollution in Los Angelesr=0.9443yrs366
Gasoline pumped in Austriar=0.9143yrs364
Air pollution in Oxnard, Californiar=0.9543yrs364
Air pollution in San Diego, Californiar=0.9443yrs363
The number of telemarketers in New Yorkr=0.9620yrs362
GMO use in cottonr=0.9323yrs362
Burglaries in New Mexicor=0.9738yrs357
Kerosene used in Brazilr=0.9242yrs354
The divorce rate in Tennesseer=0.9523yrs353
The number of telemarketers in West Virginiar=0.9620yrs352
The distance between Neptune and Mercuryr=0.9148yrs352
Burglaries in Virginiar=0.9738yrs347
Kerosene used in Egyptr=0.9242yrs344
Cottage cheese consumptionr=0.9232yrs344
The divorce rate in Wyomingr=0.9523yrs343
The number of human resources assistants in Wisconsinr=0.9720yrs342
Motor vehicle thefts in Mainer=0.9738yrs337
Kerosene used in Perur=0.9242yrs334
The marriage rate in Alabamar=0.9523yrs332
The number of human resources assistants in District of Columbiar=0.9620yrs330
Burglaries in Idahor=0.9638yrs326
Gasoline pumped in Bulgariar=0.9142yrs323
The divorce rate in Alabamar=0.9423yrs322
The number of postmasters in Marylandr=0.9620yrs320
Burglaries in Minnesotar=0.9638yrs316
Kerosene used in Uruguayr=0.9142yrs313
The divorce rate in Floridar=0.9423yrs312
The number of computer programmers in New Yorkr=0.9520yrs310
Burglaries in Arizonar=0.9638yrs306
Kerosene used globallyr=0.942yrs302
The divorce rate in Mainer=0.9423yrs302
The number of recreational therapists in New Yorkr=0.9620yrs300
Burglaries in New Jerseyr=0.9638yrs296
Kerosene used in Cubar=0.942yrs292
The divorce rate in Missourir=0.9423yrs292
The number of file clerks in New Yorkr=0.9620yrs290
Burglaries in Oklahomar=0.9638yrs286
The number of boiler operators in Wisconsinr=0.9620yrs280
The marriage rate in Arkansasr=0.9423yrs280
Petroluem consumption in Germanyr=0.9532yrs279
Burglaries in Connecticutr=0.9638yrs276
The marriage rate in Idahor=0.9423yrs270
The number of compensation and benefits managers in Wisconsinr=0.9619yrs269
Arson in Oklahomar=0.9538yrs264
Gasoline pumped in Germanyr=0.9232yrs264
The marriage rate in Nevadar=0.9423yrs260
The number of switchboard operators in Alabamar=0.9520yrs258
Arson in Texasr=0.9538yrs254
Gasoline pumped in Latviar=0.9131yrs252
The marriage rate in South Dakotar=0.9423yrs250
The number of prepress technicians and workers in Arkansasr=0.9520yrs248
Burglaries in Hawaiir=0.9538yrs244
The marriage rate in Wyomingr=0.9423yrs240
The number of postmasters in North Carolinar=0.9520yrs238
Burglaries in Nebraskar=0.9538yrs234
Liquefied petroleum gas used in Greenlandr=0.9222yrs234
The divorce rate in Illinoisr=0.9323yrs230
The number of file clerks in Ohior=0.9520yrs228
Burglaries in Utahr=0.9538yrs224
The divorce rate in New Hampshirer=0.9323yrs220
Liquefied petroleum gas used in Kosovor=0.9414yrs220
The number of special education teachers in Kansasr=0.9811yrs214
The divorce rate in Ohior=0.9323yrs210
Jet fuel used in Kosovor=0.9413yrs208
The number of career/technical education teachers, secondary school in Kansasr=0.9613yrs203
The divorce rate in Oregonr=0.9323yrs200
The number of executive administrative assistants in Tennesseer=0.9613yrs193
The divorce rate in Virginiar=0.9323yrs190


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You caught me! While it would be intuitive to sort only by "correlation," I have a big, weird database. If I sort only by correlation, often all the top results are from some one or two very large datasets (like the weather or labor statistics), and it overwhelms the page.

I can't show you *all* the correlations, because my database would get too large and this page would take a very long time to load. Instead I opt to show you a subset, and I sort them by a magic system score. It starts with the correlation, but penalizes variables that repeat from the same dataset. (It also gives a bonus to variables I happen to find interesting.)
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