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Correlations > Labor Statistics > Furniture & related product manufacturing > Production workers (average per year) (per capita)

VIEW DATA:   Totals   Per capita  
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Showing latest available data.

Correlations between Labor > Furniture & related product manufacturing > Production workers (average per year) (per capita) ...

Variable Strength
...and  Labor > Furniture & related product manufacturing > Production workers hours (per capita) 82% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Production workers wages (per $ GDP) 81% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Number of employees (per capita) 74% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Furniture and related product manufacturing (per $ GDP) 71% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total value of shipments (per $ GDP) 71% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Furniture and related product manufacturing (per $ GDP) 71% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Furniture and related product manufacturing (per capita) 71% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total cost of materials (per $ GDP) 70% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Furniture and related product manufacturing (per capita) 70% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Value added (per $ GDP) 66% [plot | correlate | graph]
...and  Industry > Textile mills > Total capital expenditures (per $ GDP) 56% [plot | correlate | graph]
...and  Industry > Textile mills > Annual payroll 56% [plot | correlate | graph]
...and  Labor > Textile mills > Production workers hours 53% [plot | correlate | graph]
...and  Industry > Textile mills > Total capital expenditures 51% [plot | correlate | graph]
...and  Industry > Textile mills > Production workers wages 50% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Annual payroll (per $ GDP) 47% [plot | correlate | graph]
...and  Labor > Beverage & tobacco product manufacturing > Production workers hours (per capita) 47% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Annual payroll (per capita) 45% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total capital expenditures (per $ GDP) 45% [plot | correlate | graph]
...and  Industry > Textile mills > Annual payroll (per $ GDP) 45% [plot | correlate | graph]
...and  Industry > Textile mills > Annual payroll (per capita) 44% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Production workers wages (per $ GDP) 41% [plot | correlate | graph]
...and  Industry > Textile mills > Total cost of materials 41% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers hours (per capita) 40% [plot | correlate | graph]
...and  Labor > Textile mills > Number of employees 40% [plot | correlate | graph]
...and  Industry > Textile mills > Total value of shipments 40% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll (per $ GDP) 39% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Food product manufacturing (per $ GDP) 39% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Food product manufacturing (per $ GDP) 39% [plot | correlate | graph]
...and  Labor > Textile mills > Production workers (average per year) 38% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll (per capita) 38% [plot | correlate | graph]
...and  Industry > Textile mills > Value added 38% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours (per capita) 37% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Value added (per $ GDP) 37% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Total value of shipments 36% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers (average per year) (per capita) 36% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers (average per year) 35% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers hours 33% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total cost of materials (per $ GDP) 32% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Production workers wages 31% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Number of employees (per capita) 31% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Number of employees (per capita) 29% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total cost of materials 29% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total value of shipments (per $ GDP) 27% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total value of shipments 27% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Value added (per $ GDP) 26% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total capital expenditures (per $ GDP) 26% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Total cost of materials (per $ GDP) 26% [plot | correlate | graph]
...and  Labor > Plastics & rubber products manufacturing > Number of employees (per capita) 25% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers hours 25% [plot | correlate | graph]
Average: 45%

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. Per capita figures expressed per 1,000 population.

SOURCE: Annual Survey of Manufactures, 2004

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