Top variables that correlate with Popularity of the first name Misty

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

Variable	Correlation	Years	Sys. Score
Carjackings in the US	r=0.97	27yrs	426
Average number of milk cows in the United States	r=0.9	43yrs	417
US birth rates of triplets or more	r=0.95	20yrs	416
The marriage rate in Tennessee	r=0.98	23yrs	416
Burglaries in Colorado	r=0.96	38yrs	416
Physical album shipment volume in the United States	r=0.96	24yrs	414
The marriage rate in Nevada	r=0.97	23yrs	414
The divorce rate in Alabama	r=0.96	23yrs	414
Kerosene used in Canada	r=0.94	43yrs	398
Kerosene used in Portugal	r=0.94	43yrs	398
Kerosene used in Turkiye	r=0.93	43yrs	397
US household spending on books	r=0.97	23yrs	394
The number of CEOs in Ohio	r=0.97	20yrs	393
The number of telemarketers in California	r=0.96	20yrs	392
The number of advertising and promotions managers in District of Columbia	r=0.97	20yrs	392
The divorce rate in Tennessee	r=0.96	23yrs	384
Burglaries in Oregon	r=0.94	38yrs	382
Google searches for 'learn spanish'	r=0.94	19yrs	378
Google searches for 'oprah winfrey'	r=0.93	19yrs	376
Google searches for 'snoop dog'	r=0.93	19yrs	376
US milk fat used to produce fluid beverage milk	r=0.91	22yrs	374
The marriage rate in South Carolina	r=0.96	23yrs	373
United States music album sales	r=0.91	16yrs	368
Kerosene used in Mexico	r=0.94	40yrs	366
Customer satisfaction with Verizon	r=0.87	28yrs	366
Customer satisfaction with Frontier Communications	r=0.85	28yrs	363
The marriage rate in Arkansas	r=0.95	23yrs	362
The number of typists in Florida	r=0.97	20yrs	362
US household spending on clothing	r=0.94	23yrs	360
US household spending on clothing for men	r=0.94	23yrs	360
Air pollution in Spokane, Washington	r=0.92	43yrs	360
Air pollution in Norwich, Connecticut	r=0.93	42yrs	360
Remaining Forest Cover in the Brazilian Amazon	r=0.87	36yrs	358
US average milk-fat content of frozen dairy products	r=0.95	22yrs	358
US household spending on processed fruits	r=0.93	23yrs	358
Air pollution in Tucson, Arizona	r=0.91	43yrs	358
US household spending on clothin for women	r=0.91	23yrs	356
Kerosene used in Norway	r=0.91	43yrs	354
The marriage rate in Ohio	r=0.95	23yrs	352
The number of typists in Iowa	r=0.97	20yrs	352
Arson in New York	r=0.92	38yrs	350
Google searches for 'report UFO sighting'	r=0.9	19yrs	348
Google searches for 'shook'	r=0.92	19yrs	344
GMO use in corn grown in South Dakota	r=0.93	23yrs	344
Kerosene used in U.S. Pacific Islands	r=0.91	42yrs	343
The number of typists in Ohio	r=0.97	20yrs	342
GMO use in corn grown in Texas	r=0.95	18yrs	342
Burglaries in Washington	r=0.92	38yrs	340
Google searches for 'desktop background'	r=0.94	16yrs	334
The number of CEOs in South Carolina	r=0.96	20yrs	332
Robberies in Oregon	r=0.92	38yrs	330
Jet fuel used in Ukraine	r=0.95	30yrs	327
Air pollution in Bridgeport, Connecticut	r=0.9	43yrs	327
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.94	22yrs	326
Google searches for 'panama canal'	r=0.91	19yrs	323
The number of switchboard operators in Wisconsin	r=0.97	20yrs	322
Burglaries in California	r=0.91	38yrs	318
Air pollution in Bridgeport, Connecticut	r=0.9	43yrs	317
Petroluem consumption in Ukraine	r=0.93	30yrs	314
Google searches for 'black holes'	r=0.91	19yrs	313
Portion of all US dairy skim-solids allocated to the production of frozen dairy products	r=0.92	22yrs	313
The number of meter readers, utilities in Alabama	r=0.96	20yrs	310
The marriage rate in South Dakota	r=0.94	23yrs	310
Google searches for 'Panama Canal'	r=0.9	19yrs	302
Petroluem consumption in Azerbaijan	r=0.91	30yrs	301
The number of postal service machine operators in Connecticut	r=0.96	20yrs	300
The marriage rate in Alabama	r=0.93	23yrs	298
Petroluem consumption in Belarus	r=0.91	30yrs	291
The number of switchboard operators in Indiana	r=0.96	20yrs	290
The marriage rate in Arizona	r=0.93	23yrs	288
The number of file clerks in Michigan	r=0.96	20yrs	280
The marriage rate in Idaho	r=0.93	23yrs	278
Burglaries in New York	r=0.89	38yrs	275
Liquefied petroleum gas used in Greenland	r=0.91	22yrs	273
The number of prepress technicians and workers in New York	r=0.96	20yrs	270
The marriage rate in Virginia	r=0.93	23yrs	268
Arson in Maine	r=0.88	38yrs	264
Geothermal power generated in Austria	r=0.91	17yrs	261
The number of prepress technicians and workers in North Carolina	r=0.96	20yrs	260
The marriage rate in Wyoming	r=0.93	23yrs	258
Burglaries in Michigan	r=0.88	38yrs	254
The number of sewing machine operators in Pennsylvania	r=0.96	20yrs	250
Gasoline pumped in Kosovo	r=0.94	14yrs	250
The divorce rate in North Carolina	r=0.92	23yrs	248
The number of switchboard operators in Tennessee	r=0.96	20yrs	240
The marriage rate in Kentucky	r=0.92	23yrs	237
Kerosene used in Bolivia	r=0.9	42yrs	232
The number of typists in Washington	r=0.96	20yrs	230
The divorce rate in Wyoming	r=0.91	23yrs	227
The number of prepress technicians and workers in Wisconsin	r=0.96	20yrs	220
Petroluem consumption in Bulgaria	r=0.89	42yrs	220
The number of compensation and benefits managers in Maine	r=0.97	19yrs	210
Petroluem consumption in Hungary	r=0.88	43yrs	210
The number of compensation and benefits managers in Indiana	r=0.96	19yrs	199
Kerosene used in Cabo Verde	r=0.88	42yrs	198
Kerosene used in Romania	r=0.88	42yrs	188
The divorce rate in Ohio	r=0.9	23yrs	186
Gasoline pumped in Bulgaria	r=0.86	42yrs	176
The divorce rate in New Hampshire	r=0.89	23yrs	174
Kerosene used in Ecuador	r=0.86	42yrs	166
The divorce rate in Oregon	r=0.89	23yrs	164

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^{What is Sys. Score?} 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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