Top variables that correlate with Popularity of the first name Dawn

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

Variable	Correlation	Years	Has img?
Air pollution in Anchorage	r=0.9	42yrs	Yes!

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

Variable	Correlation	Years	Sys. Score
Kerosene used in Canada	r=0.95	43yrs	430
Burglaries in Colorado	r=0.96	38yrs	416
The marriage rate in Tennessee	r=0.96	23yrs	413
Kerosene used in Portugal	r=0.94	43yrs	398
Kerosene used in Turkiye	r=0.92	43yrs	396
Carjackings in the US	r=0.93	27yrs	390
The number of obstetricians and gynecologists in Alabama	r=0.96	20yrs	390
The number of CEOs in Louisiana	r=0.95	20yrs	390
The number of fiberglass laminators and fabricators in North Carolina	r=0.96	20yrs	390
Average number of milk cows in the United States	r=0.88	43yrs	384
Burglaries in Oregon	r=0.94	38yrs	382
Ticket sales for Arizona Diamondbacks games	r=0.93	22yrs	379
The marriage rate in Nevada	r=0.93	23yrs	378
The marriage rate in Ohio	r=0.93	23yrs	378
Physical album shipment volume in the United States	r=0.91	24yrs	376
US Hospital Occupancy Rate	r=0.94	18yrs	375
Google searches for 'black holes'	r=0.92	19yrs	374
Kerosene used in Norway	r=0.91	43yrs	364
Customer satisfaction with Verizon	r=0.86	28yrs	364
Air pollution in Norwich, Connecticut	r=0.93	42yrs	360
The number of telephone operators in Texas	r=0.96	19yrs	359
Remaining Forest Cover in the Brazilian Amazon	r=0.87	36yrs	358
US household spending on books	r=0.93	23yrs	358
Air pollution in Bridgeport, Connecticut	r=0.91	43yrs	358
Air pollution in Bridgeport, Connecticut	r=0.91	43yrs	358
US household spending on beef	r=0.91	23yrs	356
The wind speed in Los Angeles	r=0.9	22yrs	354
Kerosene used in U.S. Pacific Islands	r=0.91	42yrs	353
Arson in New York	r=0.92	38yrs	350
The marriage rate in South Carolina	r=0.93	23yrs	348
Disney movies released	r=0.87	23yrs	347
Kerosene used in Mexico	r=0.92	40yrs	342
GMO use in corn grown in South Dakota	r=0.91	23yrs	342
Burglaries in Washington	r=0.92	38yrs	340
US milk fat used to produce fluid beverage milk	r=0.88	22yrs	340
Google searches for 'learn spanish'	r=0.89	19yrs	340
Total annual sales of Ford Motors in the United States	r=0.88	23yrs	338
The divorce rate in Alabama	r=0.91	23yrs	337
Cottage cheese consumption	r=0.87	32yrs	336
Google searches for 'E.T. phone home'	r=0.86	19yrs	336
Robberies in Oregon	r=0.92	38yrs	330
Air pollution in Spokane, Washington	r=0.91	43yrs	328
The divorce rate in Tennessee	r=0.91	23yrs	327
Jet fuel used in Ukraine	r=0.94	30yrs	326
The number of prepress technicians and workers in Alabama	r=0.95	20yrs	318
Air pollution in Tucson, Arizona	r=0.91	43yrs	318
Burglaries in California	r=0.9	38yrs	316
Petroluem consumption in Ukraine	r=0.93	30yrs	314
The number of hoist and winch operators in Florida	r=0.95	19yrs	308
Air pollution in Norwich, Connecticut	r=0.91	42yrs	308
Frozen yogurt consumption	r=0.87	32yrs	306
Petroluem consumption in Azerbaijan	r=0.9	30yrs	300
The number of advertising and promotions managers in Alabama	r=0.94	20yrs	297
Petroluem consumption in Belarus	r=0.9	30yrs	290
The number of advertising and promotions managers in California	r=0.94	20yrs	287
The marriage rate in Arkansas	r=0.9	23yrs	284
The number of advertising and promotions managers in Colorado	r=0.94	20yrs	277
Burglaries in New York	r=0.88	38yrs	274
The marriage rate in Arizona	r=0.89	23yrs	272
The number of surveying and mapping technicians in Michigan	r=0.94	20yrs	267
The marriage rate in Virginia	r=0.89	23yrs	262
Arson in Maine	r=0.87	38yrs	262
Kerosene used in Cabo Verde	r=0.89	42yrs	260
Air pollution in Miami	r=0.89	43yrs	258
The number of automotive body repairers in Michigan	r=0.94	20yrs	257
Arson in Colorado	r=0.87	38yrs	252
The marriage rate in Idaho	r=0.88	23yrs	251
Kerosene used in Bolivia	r=0.88	42yrs	248
The number of advertising and promotions managers in North Carolina	r=0.94	20yrs	247
Burglaries in Alaska	r=0.87	38yrs	242
The marriage rate in Kentucky	r=0.88	23yrs	241
Petroluem consumption in Hungary	r=0.87	43yrs	238
The number of sewing machine operators in North Carolina	r=0.94	20yrs	237
Burglaries in Michigan	r=0.87	38yrs	232
The marriage rate in New Hampshire	r=0.88	23yrs	231
The number of sewing machine operators in Virginia	r=0.94	20yrs	227
Petroluem consumption in Bulgaria	r=0.87	42yrs	227
Robberies in Michigan	r=0.87	38yrs	222
The marriage rate in Wisconsin	r=0.88	23yrs	221
Gasoline pumped in Guam	r=0.87	42yrs	217
The number of CEOs in Delaware	r=0.92	20yrs	216
The marriage rate in Alabama	r=0.87	23yrs	210
Burglaries in Montana	r=0.86	38yrs	210
The number of advertising and promotions managers in Florida	r=0.93	20yrs	206
Liquefied petroleum gas used in Netherlands Antilles	r=0.86	42yrs	206
The marriage rate in Missouri	r=0.87	23yrs	200
Burglaries in Oklahoma	r=0.86	38yrs	200
The number of prepress technicians and workers in Kansas	r=0.93	20yrs	196
Kerosene used in Romania	r=0.86	42yrs	196
The marriage rate in North Carolina	r=0.87	23yrs	190
Burglaries in Texas	r=0.86	38yrs	190
The number of advertising and promotions managers in Kentucky	r=0.94	19yrs	186
The marriage rate in South Dakota	r=0.87	23yrs	180
Motor vehicle thefts in Oklahoma	r=0.86	38yrs	180
Kerosene used in French Polynesia	r=0.88	32yrs	178
The number of couriers and messengers in Kentucky	r=0.93	20yrs	176
The marriage rate in Wyoming	r=0.87	23yrs	170
Petroluem consumption in Uzbekistan	r=0.89	30yrs	168
The number of tool and die makers in Massachusetts	r=0.93	20yrs	166
Liquefied petroleum gas used in Belarus	r=0.85	30yrs	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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