Top variables that correlate with Popularity of the first name Alisa

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

Variable	Correlation	Years	Sys. Score
Arson in United States	r=0.95	38yrs	434
Remaining Forest Cover in the Brazilian Amazon	r=0.96	36yrs	432
The distance between Neptune and the Sun	r=0.95	48yrs	418
The distance between Neptune and Earth	r=0.95	48yrs	418
The distance between Neptune and the moon	r=0.95	48yrs	418
Arson in New Jersey	r=0.96	38yrs	416
Arson in Texas	r=0.96	38yrs	416
The marriage rate in Arkansas	r=0.97	23yrs	414
The marriage rate in Virginia	r=0.97	23yrs	414
The marriage rate in Idaho	r=0.96	23yrs	413
Gasoline pumped in Austria	r=0.93	43yrs	397
Gasoline pumped in France	r=0.93	43yrs	397
Kerosene used in Thailand	r=0.93	42yrs	396
US household spending on clothing	r=0.96	23yrs	393
The number of switchboard operators in Georgia	r=0.97	20yrs	392
The number of telemarketers in Illinois	r=0.95	20yrs	390
The number of telemarketers in Kansas	r=0.95	20yrs	390
Burglaries in Hawaii	r=0.96	38yrs	386
The marriage rate in Nevada	r=0.96	23yrs	383
US birth rates of triplets or more	r=0.92	20yrs	382
Physical album shipment volume in the United States	r=0.94	24yrs	381
Milk consumption	r=0.94	32yrs	378
Google searches for 'panama canal'	r=0.94	19yrs	378
Cottage cheese consumption	r=0.94	32yrs	376
Burglaries in Idaho	r=0.95	38yrs	374
Google searches for 'Panama Canal'	r=0.92	19yrs	374
The marriage rate in South Dakota	r=0.96	23yrs	373
The wind speed in Austin	r=0.91	39yrs	373
Viewership count for Days of Our Lives	r=0.88	47yrs	370
NASA's budget as a percentage of the total US Federal Budget	r=0.86	48yrs	369
Burglaries in Arizona	r=0.95	38yrs	364
Kerosene used in Peru	r=0.91	42yrs	363
Air pollution in Los Angeles	r=0.92	43yrs	363
Air pollution in Oxnard, California	r=0.94	43yrs	363
Air pollution in New York City	r=0.91	43yrs	362
US household spending on clothing for men	r=0.94	23yrs	360
US household spending on clothin for women	r=0.94	23yrs	360
The distance between Neptune and Mercury	r=0.95	48yrs	358
The number of sewing machine operators in California	r=0.95	20yrs	358
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.95	22yrs	358
GMO use in cotton	r=0.91	23yrs	358
US household spending on books	r=0.93	23yrs	358
Kerosene used globally	r=0.9	42yrs	352
The number of floral designers in Wisconsin	r=0.95	20yrs	348
Kerosene used in Brazil	r=0.9	42yrs	342
Burglary rates in the US	r=0.93	38yrs	341
The marriage rate in Wisconsin	r=0.95	23yrs	332
Air pollution in New York City	r=0.91	43yrs	332
Motor vehicle thefts	r=0.92	38yrs	330
Petroluem consumption in Germany	r=0.94	32yrs	328
Air pollution in San Diego, California	r=0.93	43yrs	322
Robberies in the US	r=0.92	38yrs	320
The marriage rate in Kentucky	r=0.94	23yrs	320
Gasoline pumped in Germany	r=0.91	32yrs	313
Air pollution in Washington, D.C.	r=0.91	43yrs	312
The marriage rate in Ohio	r=0.94	23yrs	310
The number of computer programmers in New Jersey	r=0.95	20yrs	310
The divorce rate in Alabama	r=0.93	23yrs	300
Air pollution in Philadelphia, Pennsylvania	r=0.92	43yrs	300
The number of CEOs in Indiana	r=0.94	20yrs	298
Burglaries in Maryland	r=0.95	38yrs	294
The divorce rate in Oregon	r=0.93	23yrs	290
The number of sewing machine operators in New York	r=0.95	20yrs	288
Air pollution in Riverside, California	r=0.91	43yrs	288
Burglaries in Nebraska	r=0.95	38yrs	284
Kerosene used in Argentina	r=0.9	42yrs	282
The marriage rate in Missouri	r=0.93	23yrs	278
Air pollution in Riverside, California	r=0.91	43yrs	278
The number of telemarketers in California	r=0.93	20yrs	277
Burglaries in Utah	r=0.95	38yrs	274
Kerosene used in Egypt	r=0.9	42yrs	272
The marriage rate in South Carolina	r=0.93	23yrs	268
The number of data entry keyers in California	r=0.94	20yrs	267
Arson in Maryland	r=0.94	38yrs	262
Fossil fuel use in Sierra Leone	r=0.87	42yrs	260
The marriage rate in Tennessee	r=0.93	23yrs	258
The number of switchboard operators in Hawaii	r=0.94	20yrs	257
Burglaries in Florida	r=0.94	38yrs	252
Kerosene used in Cuba	r=0.89	42yrs	250
The marriage rate in Wyoming	r=0.93	23yrs	248
The number of floral designers in Indiana	r=0.94	20yrs	247
Burglaries in Illinois	r=0.94	38yrs	242
Kerosene used in United States	r=0.88	43yrs	240
The divorce rate in North Carolina	r=0.92	23yrs	238
The number of switchboard operators in Indiana	r=0.94	20yrs	237
Burglaries in Kansas	r=0.94	38yrs	232
Kerosene used in Uruguay	r=0.89	42yrs	230
The divorce rate in Ohio	r=0.92	23yrs	228
The number of boiler operators in Kentucky	r=0.94	20yrs	227
Burglaries in Virginia	r=0.94	38yrs	222
The divorce rate in Tennessee	r=0.92	23yrs	218
The number of advertising and promotions managers in Louisiana	r=0.94	20yrs	217
Motor vehicle thefts in Maine	r=0.94	38yrs	212
The marriage rate in Kansas	r=0.92	23yrs	207
The number of bill collectors in Massachusetts	r=0.93	20yrs	207
Motor vehicle thefts in Massachusetts	r=0.94	38yrs	202
The marriage rate in Louisiana	r=0.92	23yrs	197
The number of cooks, short order in Michigan	r=0.94	20yrs	197
Motor vehicle thefts in Michigan	r=0.94	38yrs	192
The marriage rate in Nebraska	r=0.92	23yrs	187
The number of file clerks in Missouri	r=0.94	20yrs	187

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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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