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Correlations > Energy Statistics > Electric Power Industry Emissions > SO2 (per capita)

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Correlations between Energy > Electric Power Industry Emissions > SO2 (per capita) ...

Variable Strength
...and  Energy > Electric Power Industry Emissions > SO2 (per $ GDP) 97% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > CO2 (per capita) 60% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > CO2 (per $ GDP) 56% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > NOx (per capita) 51% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total cost of materials 48% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers (average per year) (per capita) 48% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total value of shipments 47% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total capital expenditures (per $ GDP) 47% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total capital expenditures 46% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Value added 46% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers (average per year) 45% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total cost of materials (per $ GDP) 43% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > NOx (per $ GDP) 43% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total value of shipments (per $ GDP) 41% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Production workers wages (per $ GDP) 41% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Value added (per $ GDP) 40% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers hours (per capita) 40% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Production workers wages 39% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers hours 38% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total cost of materials (per $ GDP) 33% [plot | correlate | graph]
...and  Energy > Total Energy Consumption (per capita) 33% [plot | correlate | graph]
...and  Education > Postsecondary > Number Of Institutions > Two Year (per capita) 31% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Annual payroll 31% [plot | correlate | graph]
...and  Housing > Percent of Renter-occupied Units Spending 30% or More of Household Income on Rent and Utilities (inverse) 30% [plot | correlate | graph]
...and  Labor > Plastics & rubber products manufacturing > Production workers (average per year) (per capita) 30% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total value of shipments (per $ GDP) 28% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > SO2 28% [plot | correlate | graph]
...and  Energy > Coal Consumption (per capita) 28% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Motor vehicle, body, trailer, and parts manufacturing (per $ GDP) 28% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Annual payroll (per $ GDP) 27% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Motor vehicle, body, trailer, and parts manufacturing (per $ GDP) 27% [plot | correlate | graph]
...and  Energy > Coal Consumption (per $ GDP) 27% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Annual payroll (per capita) 26% [plot | correlate | graph]
...and  Energy > Fossil Fuel R & D Programs- Expenditures (per capita) 26% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials (per $ GDP) 25% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Motor vehicle, body, trailer, and parts manufacturing (per capita) 25% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Production workers wages (per $ GDP) 25% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Motor vehicle, body, trailer, and parts manufacturing (per capita) 25% [plot | correlate | graph]
...and  Economy > GSP > Chain-type Quantity Indexes > Computer and electronic product manufacturing 25% [plot | correlate | graph]
...and  Energy > Coal Consumption 25% [plot | correlate | graph]
...and  Labor > Electrical equipment, appliance, & component manufacturing > Production workers (average per year) 24% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Total cost of materials (per $ GDP) 24% [plot | correlate | graph]
...and  Industry > Leather & allied product manufacturing > Value added 23% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > CO2 23% [plot | correlate | graph]
...and  Energy > Total Electricity Consumption (per capita) 23% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total value of shipments (per $ GDP) 22% [plot | correlate | graph]
...and  Education > Public Libraries > Number of Bookmobiles (per capita) 22% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Value added (per $ GDP) 22% [plot | correlate | graph]
...and  Energy > Total Energy Consumption (per $ GDP) 22% [plot | correlate | graph]
...and  Housing > Percent of Mortgaged Owners Spending 30% or More of Household Income on Selected Monthly Owner Costs (inverse) 22% [plot | correlate | graph]
Average: 34%

About Correlations:

A correlation is a statistical measure of similarity between at least two given sets of data. StateMaster's correlations compare two variables from our database and reveal statistical relationships between them. The percentages you see represent the strength (or likelihood) that a change in the topic variable is matched by a change in the listed variables below it. But remember: These correlations do not imply causation, that is, one does not necessarily cause the other. Also, not all variables contain all states, rather subsets of states matched together.

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NOTES:

  • Outliers have been removed only where they are outside 3 standard deviations of the mean.
  • Only variable pairs where at least 15 states match for each have been considered.
  • Strength is given by the correlation coefficient (R squared). It is the fraction of variation in Y that can be attributed to the variation in X. 100% signifies a perfect fit (R squared of 1). The top 50 such stats are displayed


DEFINITION: Electric Power Industry Emissions - SO2 (Short Tons). These numbers indicate the level of emissions of sulfur dioxide (SO2)from the electric power industry. Units are short tons. Per capita figures expressed per 10,000 population.

SOURCE: National Priorities Project Database, 2001

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