Top variables that correlate with Popularity of the first name Yamilex

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

Variable	Correlation	Years	Sys. Score
Kerosene used in Uruguay	r=0.99	27yrs	420
The marriage rate in Tennessee	r=0.95	23yrs	382
Gasoline pumped in North Macedonia	r=0.94	27yrs	382
The marriage rate in Ohio	r=0.93	23yrs	378
The marriage rate in South Carolina	r=0.93	23yrs	378
Per capita consumption of margarine	r=0.97	10yrs	378
Ticket sales for Arizona Diamondbacks games	r=0.91	22yrs	376
US household spending on books	r=0.93	23yrs	358
US household spending on processed fruits	r=0.91	23yrs	356
The marriage rate in Arizona	r=0.92	23yrs	347
Kerosene used in Guyana	r=0.89	27yrs	345
Physical album shipment volume in the United States	r=0.87	24yrs	340
US Hospital Occupancy Rate	r=0.89	18yrs	338
The divorce rate in Tennessee	r=0.91	23yrs	337
Total annual sales of Ford Motors in the United States	r=0.86	23yrs	335
Season wins for the Los Angeles Chargers	r=0.96	6yrs	331
The marriage rate in Nevada	r=0.91	23yrs	326
The number of data entry keyers in Virginia	r=0.9	20yrs	321
US household spending on beef	r=0.88	23yrs	321
The number of advertising and promotions managers in California	r=0.89	20yrs	320
The number of computer programmers in Colorado	r=0.88	20yrs	320
US household spending on meats, poultry, fish, and eggs	r=0.87	23yrs	320
US household spending on pork	r=0.87	23yrs	320
US household spending on clothing for men	r=0.87	23yrs	320
US household spending on clothing	r=0.86	23yrs	318
US average milk-fat content of frozen dairy products	r=0.87	22yrs	316
Kerosene used in Mexico	r=0.87	25yrs	310
GMO use in cotton in Georgia	r=0.88	23yrs	304
Air pollution in Oxnard, California	r=0.86	26yrs	304
GMO use in cotton in North Carolina	r=0.85	23yrs	300
Liquefied petroleum gas used in Barbados	r=0.85	27yrs	299
Votes for Republican Senators in Kansas	r=0.91	9yrs	293
The number of advertising and promotions managers in Indiana	r=0.89	20yrs	290
Jet fuel used in Saint Vincent/Grenadines	r=0.85	24yrs	286
The marriage rate in Missouri	r=0.9	23yrs	284
Votes for the Democratic Presidential candidate in Louisiana	r=0.95	7yrs	284
The number of coil winders, tapers, and finishers in Pennsylvania	r=0.89	20yrs	280
The divorce rate in Alabama	r=0.88	23yrs	272
The number of data entry keyers in Arkansas	r=0.88	20yrs	268
The marriage rate in Arkansas	r=0.88	23yrs	261
The number of data entry keyers in Indiana	r=0.88	20yrs	258
Violent crime rates	r=0.78	28yrs	254
The marriage rate in Kentucky	r=0.88	23yrs	251
The number of prepress technicians and workers in Indiana	r=0.88	20yrs	248
Customer satisfaction with Frontier Communications	r=0.75	27yrs	242
The marriage rate in North Carolina	r=0.87	23yrs	240
Customer satisfaction with Verizon	r=0.74	27yrs	240
The number of fast food cooks in Michigan	r=0.88	20yrs	238
Carjackings in the US	r=0.82	27yrs	238
US birth rates of triplets or more	r=0.82	20yrs	232
Viewership count for Days of Our Lives	r=0.8	27yrs	232
The marriage rate in South Dakota	r=0.87	23yrs	230
The number of boiler operators in Michigan	r=0.88	20yrs	228
Remaining Forest Cover in the Brazilian Amazon	r=0.74	28yrs	226
US milk fat used to produce fluid beverage milk	r=0.81	22yrs	224
Burglaries in District of Columbia	r=0.85	28yrs	224
The marriage rate in Virginia	r=0.87	23yrs	220
The number of telemarketers in Texas	r=0.87	20yrs	218
The wind speed in Austin	r=0.83	28yrs	215
The marriage rate in Wisconsin	r=0.87	23yrs	210
The number of parking enforcement workers in Arizona	r=0.87	19yrs	206
The divorce rate in New Hampshire	r=0.86	23yrs	200
The number of advertising and promotions managers in Arkansas	r=0.87	20yrs	196
Robberies in Hawaii	r=0.84	28yrs	192
The marriage rate in Idaho	r=0.86	23yrs	188
The number of floral designers in Arkansas	r=0.87	20yrs	186
Robberies in Louisiana	r=0.83	28yrs	181
The marriage rate in New Hampshire	r=0.86	23yrs	178
The number of forest conservation technicians in Maryland	r=0.87	19yrs	176
Gasoline pumped in Cuba	r=0.83	27yrs	171
The divorce rate in North Carolina	r=0.85	23yrs	168
Arson in Connecticut	r=0.81	28yrs	168
The number of postal service machine operators in Maryland	r=0.87	20yrs	166
Jet fuel used in Yemen	r=0.83	27yrs	161
Motor vehicle thefts in New York	r=0.81	28yrs	158
The marriage rate in Alabama	r=0.85	23yrs	156
The number of janitors and cleaners in New Jersey	r=0.87	20yrs	156
Kerosene used in Belgium	r=0.8	28yrs	148
The marriage rate in Texas	r=0.85	23yrs	146
The number of advertising and promotions managers in North Carolina	r=0.87	20yrs	146
Robberies in New York	r=0.8	28yrs	146
Kerosene used in Cuba	r=0.81	27yrs	138
The number of advertising and promotions managers in Ohio	r=0.87	20yrs	136
Robberies in Oregon	r=0.8	28yrs	136
Kerosene used in Egypt	r=0.81	27yrs	128
The number of advertising and promotions managers in South Carolina	r=0.87	20yrs	126
Robberies in California	r=0.8	28yrs	126
Kerosene used in Nicaragua	r=0.81	27yrs	118
Arson in Oklahoma	r=0.79	28yrs	115
Kerosene used in Thailand	r=0.81	27yrs	108
Burglaries in New York	r=0.78	28yrs	104
Fossil fuel use in Sweden	r=0.78	27yrs	96
Robberies in Maryland	r=0.78	28yrs	94
Gasoline pumped in Bulgaria	r=0.8	27yrs	86
Burglaries in South Dakota	r=0.77	28yrs	82
Liquefied petroleum gas used in Greenland	r=0.83	22yrs	76
Burglaries in Connecticut	r=0.77	28yrs	72
Kerosene used in Pakistan	r=0.8	27yrs	66
Biomass power generated in Jamaica	r=0.77	27yrs	55
Kerosene used in Chile	r=0.77	28yrs	43
Kerosene used in Argentina	r=0.77	27yrs	32

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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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