Top variables that correlate with Popularity of the first name Kristie

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

Variable	Correlation	Years	Sys. Score
Kerosene used in Turkiye	r=0.97	43yrs	433
Kerosene used in Venezuela	r=0.96	42yrs	430
Kerosene used in Mexico	r=0.96	40yrs	428
Carjackings in the US	r=0.95	27yrs	423
Average number of milk cows in the United States	r=0.93	43yrs	422
Arson in New York	r=0.98	38yrs	418
Burglaries in New York	r=0.96	38yrs	416
Air pollution in Los Angeles	r=0.95	43yrs	398
Air pollution in San Diego, California	r=0.97	43yrs	398
The number of meter readers, utilities in North Carolina	r=0.97	20yrs	392
The number of typists in Washington	r=0.97	20yrs	392
US household spending on books	r=0.95	23yrs	392
Air pollution in Oxnard, California	r=0.95	41yrs	392
The number of prepress technicians and workers in Michigan	r=0.96	20yrs	390
US average milk-fat content of frozen dairy products	r=0.96	22yrs	389
Petroluem consumption in Ukraine	r=0.96	30yrs	388
Burglaries in California	r=0.95	38yrs	384
US birth rates of triplets or more	r=0.94	20yrs	384
Jet fuel used in Ukraine	r=0.96	30yrs	378
The marriage rate in Kentucky	r=0.93	23yrs	378
The marriage rate in Ohio	r=0.93	23yrs	378
The divorce rate in Tennessee	r=0.92	23yrs	378
The wind speed in Nashville	r=0.92	39yrs	374
Google searches for 'desktop background'	r=0.9	16yrs	368
Customer satisfaction with Verizon	r=0.87	28yrs	366
Customer satisfaction with Frontier Communications	r=0.86	28yrs	364
The number of advertising and promotions managers in South Carolina	r=0.96	20yrs	360
Remaining Forest Cover in the Brazilian Amazon	r=0.88	36yrs	360
US household spending on clothing	r=0.94	23yrs	360
US household spending on clothing for men	r=0.94	23yrs	360
US household spending on clothin for women	r=0.92	23yrs	357
Portion of all US dairy skim-solids allocated to the production of frozen dairy products	r=0.94	22yrs	356
Petroluem consumption in Bulgaria	r=0.94	42yrs	348
The number of typists in Alabama	r=0.95	20yrs	348
The distance between Neptune and Mercury	r=0.88	48yrs	348
The marriage rate in Arizona	r=0.92	23yrs	347
Burglaries in Colorado	r=0.95	38yrs	344
The distance between Neptune and Earth	r=0.85	48yrs	343
The distance between Neptune and the moon	r=0.85	48yrs	343
Physical album shipment volume in the United States	r=0.88	24yrs	342
GMO use in corn grown in South Dakota	r=0.91	23yrs	342
Google searches for 'shook'	r=0.9	19yrs	342
Google searches for 'learn spanish'	r=0.9	19yrs	342
Gasoline pumped in Bulgaria	r=0.94	42yrs	338
The number of prepress technicians and workers in Colorado	r=0.95	20yrs	338
The marriage rate in Nevada	r=0.92	23yrs	337
Robberies in Oregon	r=0.95	38yrs	334
Air pollution in Los Angeles	r=0.93	43yrs	334
Kerosene used in Ecuador	r=0.94	42yrs	328
The number of typists in Florida	r=0.95	20yrs	328
The marriage rate in Tennessee	r=0.92	23yrs	327
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.93	22yrs	324
Burglaries in Connecticut	r=0.94	38yrs	322
Air pollution in San Diego, California	r=0.93	43yrs	322
The number of prepress technicians and workers in New York	r=0.95	20yrs	318
Petroluem consumption in Romania	r=0.93	42yrs	316
The marriage rate in North Carolina	r=0.9	23yrs	314
Motor vehicle thefts in Massachusetts	r=0.94	38yrs	312
Air pollution in Spokane, Washington	r=0.92	43yrs	310
The number of boiler operators in North Carolina	r=0.95	20yrs	308
Gasoline pumped in Somalia	r=0.93	42yrs	306
US milk fat used to produce fluid beverage milk	r=0.89	22yrs	302
Burglaries in Texas	r=0.93	38yrs	301
The number of typists in Wisconsin	r=0.95	20yrs	298
Kerosene used in Uruguay	r=0.92	42yrs	294
Air pollution in Steamboat Springs, Colorado	r=0.9	38yrs	292
Motor vehicle thefts in Oklahoma	r=0.93	38yrs	291
Kerosene used in Argentina	r=0.91	42yrs	283
Robberies in New York	r=0.93	38yrs	281
The marriage rate in South Carolina	r=0.9	23yrs	274
Gasoline pumped in Cuba	r=0.91	42yrs	273
Burglaries in Oregon	r=0.92	38yrs	270
The divorce rate in Alabama	r=0.89	23yrs	264
Kerosene used in Hong Kong	r=0.91	42yrs	263
Burglaries in Rhode Island	r=0.92	38yrs	260
The number of CEOs in Ohio	r=0.95	20yrs	260
The divorce rate in New Hampshire	r=0.89	23yrs	254
Kerosene used in Cuba	r=0.9	42yrs	252
Arson in Colorado	r=0.91	38yrs	248
The number of computer programmers in Colorado	r=0.94	20yrs	248
The marriage rate in Alabama	r=0.89	23yrs	242
Burglaries in New Mexico	r=0.91	38yrs	238
The number of telemarketers in Illinois	r=0.94	20yrs	238
Petroluem consumption in Belarus	r=0.94	30yrs	236
The marriage rate in Idaho	r=0.89	23yrs	232
Burglaries in Oklahoma	r=0.91	38yrs	228
The number of postal service machine operators in Maryland	r=0.95	20yrs	228
Kerosene used in French Polynesia	r=0.91	32yrs	223
Motor vehicle thefts in New Jersey	r=0.91	38yrs	218
The number of telephone operators in New York	r=0.95	19yrs	218
Petroluem consumption in Azerbaijan	r=0.92	30yrs	212
Motor vehicle thefts in Rhode Island	r=0.91	38yrs	208
The number of sewing machine operators in New York	r=0.95	20yrs	208
Robberies in Michigan	r=0.91	38yrs	198
The number of sewing machine operators in Pennsylvania	r=0.95	20yrs	198
Jet fuel used in Saint Vincent/Grenadines	r=0.92	24yrs	196
The number of switchboard operators in Tennessee	r=0.95	20yrs	188
Burglaries in Florida	r=0.9	38yrs	186
Geothermal power generated in Austria	r=0.9	17yrs	180
The number of human resources assistants in Vermont	r=0.95	20yrs	178
The number of telemarketers in California	r=0.93	20yrs	167

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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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