FACTOID # 2: Wisconsin has more metal fabricators per capita than any other state.
 
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Correlations > Labor Statistics > Electrical equipment, appliance, & component manufacturing > Production workers (average per year)

VIEW DATA:   Totals   Per capita  
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Showing latest available data.

Correlations between Labor > Electrical equipment, appliance, & component manufacturing > Production workers (average per year) ...

Variable Strength
...and  Labor > Electrical equipment, appliance, & component manufacturing > Production workers hours 66% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Value added 63% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total value of shipments 62% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total cost of materials 59% [plot | correlate | graph]
...and  Industry > Food manufacturing > Production workers wages 58% [plot | correlate | graph]
...and  Industry > Food manufacturing > Annual payroll 56% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Electrical equipment and appliance manufacturing 54% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Electrical equipment and appliance manufacturing 54% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Number of employees 53% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Food product manufacturing 51% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Electrical equipment and appliance manufacturing 51% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Truck transportation 51% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Annual payroll 49% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Plastics and rubber products manufacturing 48% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Plastics and rubber products manufacturing 48% [plot | correlate | graph]
...and  Industry > Food manufacturing > Total capital expenditures 48% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Annual payroll 48% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total cost of materials 46% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Electrical equipment and appliance manufacturing 46% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Plastics and rubber products manufacturing 46% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Plastics and rubber products manufacturing 45% [plot | correlate | graph]
...and  Labor > Machinery manufacturing > Production workers (average per year) 45% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Production workers wages 44% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Annual payroll 44% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Paper manufacturing 43% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total capital expenditures 43% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total capital expenditures 42% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers hours 42% [plot | correlate | graph]
...and  Education > Public Libraries > Circulation of Children's Materials 42% [plot | correlate | graph]
...and  Labor > Nonmetallic mineral product manufacturing > Production workers (average per year) 42% [plot | correlate | graph]
...and  Labor > Electrical equipment, appliance, & component manufacturing > Number of employees 42% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers (average per year) 42% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Motor vehicle, body, trailer, and parts manufacturing 42% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Motor vehicle, body, trailer, and parts manufacturing 42% [plot | correlate | graph]
...and  Labor > Machinery manufacturing > Production workers hours 42% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Fabricated metal product manufacturing 42% [plot | correlate | graph]
...and  Energy > Electric Power Industry Emissions > SO2 42% [plot | correlate | graph]
...and  Industry > Miscellaneous manufacturing > Production workers wages 41% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials 41% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total cost of materials 41% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total value of shipments 41% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Paper manufacturing 40% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Paper manufacturing 40% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total value of shipments 40% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Value added 40% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total value of shipments 40% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Primary metal manufacturing 39% [plot | correlate | graph]
...and  Labor > Miscellaneous manufacturing > Production workers (average per year) 39% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total value of shipments 39% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Primary metal manufacturing 39% [plot | correlate | graph]
Average: 46%

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: This item includes all full-time and part-time employees on the payrolls of operating manufacturing establishments during any part of the pay period that included the 12th of the months specified on the report form. Included are employees on paid sick leave, paid holidays, and paid vacations; not included are proprietors and partners of unincorporated businesses.

SOURCE: Annual Survey of Manufactures, 2004

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