FACTOID # 2: Wisconsin has more metal fabricators per capita than any other state.
 
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Correlations > Labor Statistics > Paper manufacturing > Number of employees

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Showing latest available data.

Correlations between Labor > Paper manufacturing > Number of employees ...

Variable Strength
...and  Labor > Paper manufacturing > Production workers (average per year) 70% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Paper manufacturing 70% [plot | correlate | graph]
...and  Labor > Electrical equipment, appliance, & component manufacturing > Number of employees 69% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Total cost of materials 64% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Production workers hours 63% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Paper manufacturing 59% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Paper manufacturing 59% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Electrical equipment and appliance manufacturing 58% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Electrical equipment and appliance manufacturing 58% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Total value of shipments 58% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Production workers wages 57% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total value of shipments 56% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total cost of materials 56% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total capital expenditures 54% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Electrical equipment and appliance manufacturing 52% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Electrical equipment and appliance manufacturing 51% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours 51% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Value added 51% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Value added 51% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Annual payroll 50% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Plastics and rubber products manufacturing 48% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Annual payroll 48% [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  Economy > GSP > Real GSP > Machinery manufacturing 48% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Machinery manufacturing 48% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Truck transportation 48% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total value of shipments 47% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total capital expenditures 47% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Value added 47% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials 46% [plot | correlate | graph]
...and  Labor > Plastics & rubber products manufacturing > Production workers (average per year) 46% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total cost of materials 45% [plot | correlate | graph]
...and  Industry > Printing & related support activities > Total capital expenditures 45% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Production workers wages 45% [plot | correlate | graph]
...and  Labor > Electrical equipment, appliance, & component manufacturing > Production workers hours 45% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Value added 44% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Truck transportation 44% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Truck transportation 44% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Machinery manufacturing 43% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total capital expenditures 43% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total value of shipments 43% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Plastics and rubber products manufacturing 42% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Number of employees 42% [plot | correlate | graph]
...and  Health > Gonorrhea Cases 41% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total value of shipments 41% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Value added 40% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total cost of materials 40% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Annual payroll 40% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total value of shipments 39% [plot | correlate | graph]
Average: 50%

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.

VIEW FOR THIS VARIABLE:

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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