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Correlations > Labor Statistics > Furniture & related product 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 > Furniture & related product manufacturing > Production workers hours ...

Variable Strength
...and  Industry > Furniture & related product manufacturing > Production workers wages 90% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers (average per year) 86% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Number of employees 79% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Furniture and related product manufacturing 78% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Furniture and related product manufacturing 74% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Furniture and related product manufacturing 74% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total cost of materials 74% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Total value of shipments 72% [plot | correlate | graph]
...and  Labor > Beverage & tobacco product manufacturing > Production workers hours 68% [plot | correlate | graph]
...and  Industry > Textile product mills > Total capital expenditures 67% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total value of shipments 67% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Food product manufacturing 67% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Food product manufacturing 67% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total capital expenditures 65% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Production workers wages 62% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Value added 61% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Annual payroll 58% [plot | correlate | graph]
...and  Industry > Textile product mills > Value added 56% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Nonmetallic mineral product manufacturing 54% [plot | correlate | graph]
...and  Labor > Textile product mills > Number of employees 54% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Production workers (average per year) 54% [plot | correlate | graph]
...and  Labor > Nonmetallic mineral product manufacturing > Number of employees 53% [plot | correlate | graph]
...and  Industry > Textile product mills > Production workers wages 52% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Wood product manufacturing 52% [plot | correlate | graph]
...and  Health > Total Dual Eligible Medicaid Spending 52% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Value added 52% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours 51% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Production workers hours 50% [plot | correlate | graph]
...and  Labor > Nonmetallic mineral product manufacturing > Production workers hours 50% [plot | correlate | graph]
...and  Industry > Leather & allied product manufacturing > Total capital expenditures 50% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Wood product manufacturing 49% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Annual payroll 49% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Wood product manufacturing 49% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Truck transportation 49% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Truck transportation 49% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Furniture and related product manufacturing 49% [plot | correlate | graph]
...and  Health > Total Medicaid Spending, FY2004 49% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Value added 48% [plot | correlate | graph]
...and  Labor > Textile product mills > Production workers hours 48% [plot | correlate | graph]
...and  Military > DOD Inactive Military Employees > Salaries & Wages 48% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Truck transportation 48% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Number of employees 48% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Production workers wages 47% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers (average per year) 47% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Total cost of materials 47% [plot | correlate | graph]
...and  Health > Total State Health Care Spending 47% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total capital expenditures 47% [plot | correlate | graph]
...and  Industry > Textile product mills > Total value of shipments 47% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Nonmetallic mineral product manufacturing 46% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Nonmetallic mineral product manufacturing 46% [plot | correlate | graph]
Average: 57%

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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