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Correlations > Labor Statistics > Apparel manufacturing > Production workers hours

DEFINITION: This item covers all hours worked or paid for at the manufacturing plant, including actual overtime hours (not straight-time equivalent hours). It excludes hours paid for vacations, holidays, or sick leave when the employee is not at the establishment.
VIEW DATA:   Totals   Per capita  
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Showing latest available data.

Correlations between Labor > Apparel manufacturing > Production workers hours ...

Variable Strength
...and  Industry > Apparel manufacturing > Production workers wages 99% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Value added 94% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total value of shipments 89% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll 88% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Number of employees 87% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total cost of materials 87% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Apparel manufacturing 85% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers (average per year) 83% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Apparel manufacturing 80% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Apparel manufacturing 80% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Apparel manufacturing (per capita) 77% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Apparel manufacturing (per capita) 77% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Apparel manufacturing 65% [plot | correlate | graph]
...and  Health > ADAP Insurance Purchasing/Maintenance Funds 65% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Apparel manufacturing (per capita) 65% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll (per capita) 62% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Apparel manufacturing (per $ GDP) 60% [plot | correlate | graph]
...and  Industry > Textile product mills > Value added 60% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Apparel manufacturing (per $ GDP) 59% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers hours (per capita) 58% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Number of employees (per capita) 56% [plot | correlate | graph]
...and  Labor > Textile product mills > Number of employees 54% [plot | correlate | graph]
...and  Industry > Textile product mills > Total value of shipments 53% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers (average per year) 52% [plot | correlate | graph]
...and  Industry > Textile product mills > Annual payroll 52% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Apparel manufacturing (per $ GDP) 52% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Production workers wages (per $ GDP) 51% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers (average per year) (per capita) 48% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Annual payroll 48% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Textile and textile product mills 48% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Textile and textile product mills 48% [plot | correlate | graph]
...and  Industry > Textile product mills > Production workers wages 47% [plot | correlate | graph]
...and  Labor > Beverage & tobacco product manufacturing > Production workers (average per year) 47% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Production workers wages 47% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Number of employees 47% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll (per $ GDP) 46% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total cost of materials (per $ GDP) 46% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Federal Reserve banks, credit intermediation and related services 45% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Federal Reserve banks, credit intermediation and related services 45% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total value of shipments (per $ GDP) 45% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Furniture and related product manufacturing 44% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Value added 44% [plot | correlate | graph]
...and  Energy > Renewable Hydroelectric Production 43% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Chemical manufacturing 43% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Annual payroll 42% [plot | correlate | graph]
...and  Health > Baseline Dual Eligible Enrollment 42% [plot | correlate | graph]
...and  Industry > Textile product mills > Total capital expenditures 41% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Value added (per $ GDP) 41% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Furniture and related product manufacturing 40% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Furniture and related product manufacturing 40% [plot | correlate | graph]
Average: 58%

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
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