Top variables that correlate with Popularity of the first name Fidel

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

Variable	Correlation	Years	Sys. Score
Gasoline pumped in Switzerland	r=0.92	43yrs	396
Kerosene used in Japan	r=0.91	43yrs	394
Lloyds Banking Group's stock price (LYG)	r=0.9	21yrs	392
The number of brickmasons in South Carolina	r=0.97	20yrs	392
Gasoline pumped in Italy	r=0.9	43yrs	392
The number of telemarketers in California	r=0.95	20yrs	390
The number of payroll and timekeeping clerks in Georgia	r=0.96	20yrs	390
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.96	22yrs	389
Portion of all US dairy skim-solids allocated to the production of frozen dairy products	r=0.95	22yrs	388
US average milk-fat content of cottage cheese	r=0.95	22yrs	388
US birth rates of triplets or more	r=0.93	20yrs	383
U.S. intercountry adoptions	r=0.95	23yrs	382
Physical album shipment volume in the United States	r=0.94	24yrs	381
The marriage rate in Wyoming	r=0.94	23yrs	380
The marriage rate in Idaho	r=0.93	23yrs	378
The divorce rate in North Carolina	r=0.92	23yrs	378
Motor vehicle thefts in Maryland	r=0.91	38yrs	378
Robberies in Arizona	r=0.91	38yrs	378
Robberies in South Carolina	r=0.91	38yrs	378
Google searches for 'learn spanish'	r=0.93	19yrs	376
Google searches for 'snoop dog'	r=0.92	19yrs	374
Cigarette Smoking Rate for US adults	r=0.9	21yrs	372
GMO use in cotton	r=0.94	23yrs	363
The number of file clerks in Massachusetts	r=0.96	20yrs	360
Citigroup's stock price (C)	r=0.89	21yrs	360
AIG's stock price (AIG)	r=0.89	21yrs	360
Number of edits to the Wikipedia article for Thanksgiving	r=0.89	16yrs	360
Kerosene used in Central African Republic	r=0.93	35yrs	359
US household spending on clothing	r=0.91	23yrs	356
US household spending on clothin for women	r=0.91	23yrs	356
The number of prepress technicians and workers in Massachusetts	r=0.96	20yrs	350
Kerosene used in Montserrat	r=0.93	35yrs	349
The divorce rate in Alabama	r=0.91	23yrs	347
US milk fat used to produce fluid beverage milk	r=0.92	22yrs	346
GMO use in corn grown in Iowa	r=0.91	23yrs	342
GMO use in corn grown in Minnesota	r=0.91	23yrs	342
The number of postal service machine operators in New Jersey	r=0.96	20yrs	340
Nuclear power generation in Germany	r=0.93	31yrs	338
The divorce rate in Wyoming	r=0.91	23yrs	337
Ice cream consumption	r=0.93	32yrs	335
Arson in Idaho	r=0.93	22yrs	335
The number of boiler operators in Ohio	r=0.96	20yrs	330
The marriage rate in Arkansas	r=0.91	23yrs	326
Sherbet consumption	r=0.92	32yrs	324
Gasoline pumped in Slovenia	r=0.91	31yrs	322
The number of postal service machine operators in Oklahoma	r=0.96	20yrs	320
The marriage rate in Nevada	r=0.9	23yrs	314
GMO use in cotton in Texas	r=0.93	23yrs	312
The number of postal service machine operators in Washington	r=0.96	20yrs	310
Motor vehicle thefts in North Carolina	r=0.9	38yrs	306
Liquefied petroleum gas used in Greenland	r=0.92	22yrs	304
GMO use in corn grown in Texas	r=0.93	18yrs	300
The number of compensation and benefits managers in Oregon	r=0.96	19yrs	299
US average milk-fat content of milk fat and skim solids byproduct fluid beverage milk	r=0.94	22yrs	296
Robberies in North Carolina	r=0.89	38yrs	295
Geothermal power generated in Austria	r=0.91	17yrs	291
GMO use in cotton in North Carolina	r=0.92	23yrs	290
The number of meter readers, utilities in Alabama	r=0.95	20yrs	288
US average milk-fat content of frozen dairy products	r=0.94	22yrs	286
Arson in Missouri	r=0.88	38yrs	284
The number of postal service machine operators in California	r=0.95	20yrs	278
The divorce rate in Arkansas	r=0.9	23yrs	276
Petroluem consumption in Japan	r=0.88	48yrs	274
Motor vehicle thefts in Georgia	r=0.88	38yrs	274
The number of data entry keyers in Connecticut	r=0.95	20yrs	268
The divorce rate in Kentucky	r=0.9	23yrs	266
Electricity generation in U.S. Virgin Islands	r=0.89	42yrs	263
Robberies in Pennsylvania	r=0.87	38yrs	262
US production of cottage cheese	r=0.88	22yrs	260
The number of proofreaders in Connecticut	r=0.95	20yrs	258
The divorce rate in Florida	r=0.89	23yrs	254
Fossil fuel use in U.S. Virgin Islands	r=0.89	42yrs	253
Robberies in Virginia	r=0.87	38yrs	252
Milk consumption	r=0.88	32yrs	249
The number of data entry keyers in District of Columbia	r=0.95	20yrs	248
The divorce rate in Mississippi	r=0.89	23yrs	244
Gasoline pumped in Denmark	r=0.9	43yrs	242
Robberies in Alabama	r=0.86	38yrs	240
The number of postal service machine operators in Iowa	r=0.95	20yrs	238
US dairy skim solids used to produce cottage cheese	r=0.88	22yrs	238
The marriage rate in South Dakota	r=0.89	23yrs	232
Gasoline pumped in Spain	r=0.89	43yrs	231
Burglaries in North Carolina	r=0.85	38yrs	229
The number of postal service machine operators in Kansas	r=0.95	20yrs	228
The divorce rate in Oregon	r=0.88	23yrs	222
Gasoline pumped in Sweden	r=0.88	43yrs	220
The number of postal service machine operators in Nebraska	r=0.95	20yrs	218
The marriage rate in Alabama	r=0.88	23yrs	211
The number of postal service machine operators in North Dakota	r=0.95	20yrs	208
Kerosene used in Indonesia	r=0.88	42yrs	208
The marriage rate in Kansas	r=0.88	23yrs	201
The number of switchboard operators in Virginia	r=0.95	20yrs	198
Kerosene used in Vietnam	r=0.88	42yrs	198
The marriage rate in Virginia	r=0.88	23yrs	191
Kerosene used in Tunisia	r=0.87	42yrs	187
The marriage rate in West Virginia	r=0.88	23yrs	181
Fossil fuel use in Slovakia	r=0.9	29yrs	172
The marriage rate in Louisiana	r=0.87	23yrs	170
The divorce rate in Idaho	r=0.86	23yrs	160
Gasoline pumped in Latvia	r=0.88	31yrs	158
The divorce rate in Ohio	r=0.86	23yrs	150

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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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