Top variables that correlate with The number of data entry keyers in North Dakota

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Data source: Bureau of Larbor Statistics
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The number of data entry keyers in North Dakota correlates with...

Variable	Correlation	Years	Sys. Score
Remaining Forest Cover in the Brazilian Amazon	r=0.93	20yrs	382
US birth rates of triplets or more	r=0.91	19yrs	379
GMO use in cotton	r=0.91	20yrs	376
The distance between Neptune and the Sun	r=0.92	20yrs	376
Popularity of the first name Bryant	r=0.94	20yrs	376
Popularity of the first name Haleigh	r=0.94	20yrs	376
Electricity generation in U.S. Virgin Islands	r=0.93	19yrs	376
Fossil fuel use in U.S. Virgin Islands	r=0.93	19yrs	376
The distance between Neptune and Earth	r=0.91	20yrs	374
The distance between Neptune and the moon	r=0.91	20yrs	374
Popularity of the first name Alexis	r=0.93	20yrs	374
Kerosene used in Macau	r=0.93	19yrs	373
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.93	19yrs	372
US household spending on books	r=0.91	20yrs	372
Portion of all US dairy skim-solids allocated to the production of frozen dairy products	r=0.92	19yrs	370
Arson in United States	r=0.89	20yrs	347
Ice cream consumption	r=0.89	19yrs	346
Google searches for 'report UFO sighting'	r=0.89	19yrs	346
Popularity of the first name Sabrina	r=0.93	20yrs	344
Viewership count for Days of Our Lives	r=0.88	19yrs	342
Gasoline pumped in Norway	r=0.91	20yrs	341
US household spending on processed fruits	r=0.9	20yrs	341
Physical album shipment volume in the United States	r=0.88	20yrs	338
Google searches for 'oprah winfrey'	r=0.88	19yrs	338
US household spending on postage and stationery	r=0.88	20yrs	338
Automotive recalls for issues with Vehicle Speed Control	r=0.86	20yrs	335
US household spending on prescription drugs	r=0.86	20yrs	335
Popularity of the first name Caitlin	r=0.93	20yrs	334
U.S. intercountry adoptions	r=0.86	19yrs	334
Kerosene used in Norway	r=0.91	20yrs	331
Popularity of the first name Colin	r=0.93	20yrs	324
Kerosene used in Hong Kong	r=0.91	19yrs	320
Popularity of the first name Brendan	r=0.93	20yrs	314
Milk consumption	r=0.86	19yrs	313
Kerosene used globally	r=0.9	19yrs	308
Popularity of the first name Colby	r=0.93	20yrs	304
Google searches for 'desktop background'	r=0.86	16yrs	302
Kerosene used in Thailand	r=0.9	19yrs	298
US average milk-fat content of frozen dairy products	r=0.9	19yrs	297
Popularity of the first name Jakob	r=0.93	20yrs	294
US average milk-fat content of milk fat and skim solids byproduct fluid beverage milk	r=0.89	19yrs	286
Popularity of the first name Abbey	r=0.93	20yrs	284
How 'hip and with it' Computerphile YouTube video titles are	r=0.88	10yrs	284
Popularity of the first name Tess	r=0.93	20yrs	274
US milk fat used to produce fluid beverage milk	r=0.85	19yrs	272
Popularity of the first name Kolby	r=0.93	20yrs	264
Divorce rates in the United Kingdom	r=0.86	10yrs	262
Nuclear power generation in Germany	r=0.89	19yrs	260
Popularity of the first name Kristyn	r=0.93	20yrs	254
Gasoline pumped in Switzerland	r=0.9	20yrs	250
Popularity of the first name Keshawn	r=0.93	20yrs	244
Kerosene used in South Korea	r=0.89	20yrs	238
Popularity of the first name Jimmie	r=0.93	20yrs	234
Burglary rates in the US	r=0.83	20yrs	233
Viewership count of American Idol Season Finale	r=0.83	20yrs	230
Cigarette Smoking Rate for US adults	r=0.85	19yrs	228
Fossil fuel use in Denmark	r=0.87	19yrs	227
US household spending on fresh milk and cream	r=0.84	20yrs	227
Popularity of the first name Cydney	r=0.93	20yrs	224
Kerosene used in Malawi	r=0.89	19yrs	217
Popularity of the first name Lexis	r=0.93	20yrs	214
Kerosene used in Bangladesh	r=0.88	19yrs	206
Popularity of the first name Janel	r=0.93	20yrs	204
Robberies in the US	r=0.82	20yrs	202
Carjackings in the US	r=0.82	19yrs	200
The distance between Neptune and Mercury	r=0.84	20yrs	198
NASA's budget as a percentage of the total US Federal Budget	r=0.81	20yrs	198
Liquefied petroleum gas used in Djibouti	r=0.88	19yrs	196
Google searches for 'panama canal'	r=0.83	19yrs	196
Popularity of the first name Kelci	r=0.93	20yrs	194
US household spending on beef	r=0.82	20yrs	194
US household spending on mortgage interest and charges	r=0.82	20yrs	194
US household spending on clothing	r=0.82	20yrs	194
Global Per Capita Rice Consumption	r=0.83	17yrs	192
US household spending on natural gas	r=0.81	20yrs	192
US household spending on floor coverings	r=0.81	20yrs	192
GMO use in cotton	r=0.78	20yrs	191
United States music album sales	r=0.82	16yrs	190
The marriage rate in North Dakota	r=0.8	19yrs	190
Gasoline pumped in Italy	r=0.88	20yrs	186
Popularity of the first name Brandon	r=0.92	20yrs	182
Kerosene used in Japan	r=0.88	20yrs	176
Liquefied petroleum gas used in Norway	r=0.88	20yrs	166
Google searches for 'learn spanish'	r=0.83	19yrs	166
Gasoline pumped in Portugal	r=0.88	20yrs	156
Google searches for 'life insurance quotes'	r=0.82	19yrs	154
The distance between Neptune and Saturn	r=0.8	20yrs	152
Gasoline pumped in Sweden	r=0.88	20yrs	146
Google searches for 'xbox'	r=0.82	19yrs	144
US household spending on clothin for women	r=0.8	20yrs	141
US household spending on vehicle insurance	r=0.79	20yrs	135
Google searches for 'matt parker'	r=0.82	19yrs	134
Cottage cheese consumption	r=0.82	19yrs	130
Google searches for 'black holes'	r=0.82	19yrs	124
Sherbet consumption	r=0.79	19yrs	116
Google searches for 'Panama Canal'	r=0.81	19yrs	113
Portion of all US dairy skim-solids allocated to the production of cottage cheese	r=0.83	19yrs	102
Google searches for 'shook'	r=0.8	19yrs	102
US production of fluid beverage milk	r=0.79	19yrs	88
Google searches for 'snoop dog'	r=0.78	19yrs	88
US production of cottage cheese	r=0.79	19yrs	78

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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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