Top variables that correlate with Popularity of the first name Stephan

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

Variable	Correlation	Years	Has img?
Remaining Forest Cover in the Brazilian Amazon	r=0.96	36yrs	No
Arson in United States	r=0.95	38yrs	No
Motor vehicle thefts in Illinois	r=0.95	38yrs	No
Frozen yogurt consumption	r=0.94	32yrs	No
Violent crime rates	r=0.93	38yrs	No
Petroluem consumption in North Korea	r=0.92	42yrs	No

Popularity of the first name Stephan also correlates with...

Variable	Correlation	Years	Sys. Score
Kerosene used in Pakistan	r=0.95	42yrs	429
Carjackings in the US	r=0.96	27yrs	424
Kerosene used in Egypt	r=0.94	42yrs	398
Jet fuel used in Germany, West	r=0.95	11yrs	398
Burglaries in Connecticut	r=0.98	38yrs	388
The marriage rate in Arizona	r=0.94	23yrs	380
The marriage rate in Nevada	r=0.94	23yrs	380
The marriage rate in Tennessee	r=0.94	23yrs	380
The wind speed in Austin	r=0.95	39yrs	379
Physical album shipment volume in the United States	r=0.92	24yrs	378
Motor vehicle thefts in New Jersey	r=0.98	38yrs	378
The wind speed in San Diego	r=0.93	39yrs	376
Burglaries in New York	r=0.97	38yrs	367
Customer satisfaction with Frontier Communications	r=0.87	28yrs	366
Customer satisfaction with Verizon	r=0.86	28yrs	364
Kerosene used in Argentina	r=0.92	42yrs	364
US household spending on books	r=0.95	23yrs	362
Air pollution in Santa Maria, California	r=0.93	43yrs	362
The number of legislators in Indiana	r=0.94	20yrs	358
Air pollution in Santa Maria, California	r=0.91	42yrs	358
The number of prepress technicians and workers in New York	r=0.94	20yrs	357
Motor vehicle thefts in Massachusetts	r=0.97	38yrs	357
The number of data entry keyers in California	r=0.93	20yrs	356
US household spending on clothing	r=0.91	23yrs	356
US household spending on clothing for men	r=0.91	23yrs	356
Air pollution in Steamboat Springs, Colorado	r=0.92	38yrs	355
US average milk-fat content of frozen dairy products	r=0.93	22yrs	354
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.92	22yrs	353
The divorce rate in Alabama	r=0.93	23yrs	350
Robberies in New York	r=0.97	38yrs	347
Kerosene used in North Korea	r=0.92	42yrs	344
US birth rates of triplets or more	r=0.86	20yrs	342
GMO use in corn grown in South Dakota	r=0.91	23yrs	342
Total annual sales of Ford Motors in the United States	r=0.89	23yrs	340
Google searches for 'panama canal'	r=0.89	19yrs	340
Ticket sales for Arizona Diamondbacks games	r=0.87	22yrs	340
The marriage rate in Ohio	r=0.93	23yrs	338
Burglaries in District of Columbia	r=0.96	38yrs	336
Gasoline pumped in France	r=0.9	43yrs	332
The divorce rate in Tennessee	r=0.92	23yrs	328
The number of telemarketers in Illinois	r=0.92	20yrs	326
Motor vehicle thefts in New York	r=0.96	38yrs	326
Portion of all US dairy skim-solids allocated to the production of frozen dairy products	r=0.92	22yrs	323
The marriage rate in Idaho	r=0.92	23yrs	317
The number of data entry keyers in Nebraska	r=0.93	20yrs	316
Burglaries in New Jersey	r=0.95	38yrs	314
Petroluem consumption in Azerbaijan	r=0.9	30yrs	310
The marriage rate in Virginia	r=0.92	23yrs	307
The number of human resources assistants in Ohio	r=0.93	20yrs	306
Robberies in Washington	r=0.95	38yrs	304
US milk fat used to produce fluid beverage milk	r=0.89	22yrs	302
The marriage rate in Arkansas	r=0.91	23yrs	296
The number of photographers in Arkansas	r=0.92	20yrs	294
The marriage rate in South Carolina	r=0.91	23yrs	286
The number of telephone operators in Florida	r=0.93	19yrs	284
Kerosene used in Thailand	r=0.9	42yrs	282
Robberies in the US	r=0.94	38yrs	282
The marriage rate in Kentucky	r=0.9	23yrs	274
The number of switchboard operators in Georgia	r=0.92	20yrs	274
Gasoline pumped in Austria	r=0.89	43yrs	271
Burglary rates in the US	r=0.93	38yrs	271
The marriage rate in Missouri	r=0.9	23yrs	264
The number of advertising and promotions managers in Louisiana	r=0.92	20yrs	264
Jet fuel used in Afghanistan	r=0.89	42yrs	260
Motor vehicle thefts	r=0.92	38yrs	260
The number of file clerks in Maryland	r=0.92	20yrs	254
Kerosene used in Cuba	r=0.87	42yrs	247
The number of prepress technicians and workers in North Carolina	r=0.92	20yrs	244
Gasoline pumped in North Korea	r=0.87	42yrs	237
The number of proofreaders in Pennsylvania	r=0.92	20yrs	234
Burglaries in Florida	r=0.95	38yrs	234
The number of proofreaders in Wisconsin	r=0.92	20yrs	224
Gasoline pumped in Cuba	r=0.85	42yrs	224
Motor vehicle thefts in Texas	r=0.95	38yrs	224
The marriage rate in Alabama	r=0.89	23yrs	222
Motor vehicle thefts in Texas	r=0.95	38yrs	214
The number of travel agents in California	r=0.91	20yrs	212
The marriage rate in North Carolina	r=0.89	23yrs	212
Petroluem consumption in Uzbekistan	r=0.9	30yrs	210
Motor vehicle thefts in Texas	r=0.95	38yrs	204
The number of travel agents in Connecticut	r=0.91	20yrs	202
The marriage rate in South Dakota	r=0.89	23yrs	202
Gasoline pumped in Germany	r=0.88	32yrs	198
The number of cashiers in Indiana	r=0.91	20yrs	192
The marriage rate in Wisconsin	r=0.88	23yrs	191
Jet fuel used in Ukraine	r=0.89	30yrs	188
The number of couriers and messengers in Indiana	r=0.91	20yrs	182
The marriage rate in Wyoming	r=0.88	23yrs	181
Petroluem consumption in Ukraine	r=0.86	30yrs	174
The number of data entry keyers in Maryland	r=0.91	20yrs	172
The divorce rate in New Hampshire	r=0.87	23yrs	171
The number of prepress technicians and workers in Massachusetts	r=0.91	20yrs	162
Gasoline pumped in Eritrea	r=0.86	28yrs	162
The divorce rate in North Carolina	r=0.86	23yrs	160
Liquefied petroleum gas used in Greenland	r=0.9	22yrs	152

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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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