FACTOID # 3: Looking for table makers? Head to Mississippi, with an overwhlemingly large number of employees in furniture manufacturing.
 
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Correlations > Labor Statistics > Wood product manufacturing > Number of employees

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.
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Showing latest available data.

Correlations between Labor > Wood product manufacturing > Number of employees ...

Variable Strength
...and  Labor > Wood product manufacturing > Production workers (average per year) 87% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Wood product manufacturing 86% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Wood product manufacturing 86% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Wood product manufacturing 86% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Annual payroll 86% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Value added 86% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Total value of shipments 83% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Production workers wages 82% [plot | correlate | graph]
...and  Labor > Wood product manufacturing > Production workers hours 80% [plot | correlate | graph]
...and  Industry > Wood product manufacturing > Total cost of materials 77% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Wood product manufacturing 73% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Total cost of materials 55% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Total value of shipments 53% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Nonmetallic mineral product manufacturing 52% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Annual payroll 52% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Forestry, fishing, and related activities 52% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Paper manufacturing 50% [plot | correlate | graph]
...and  Industry > Paper manufacturing > Value added 50% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Value added 49% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Paper manufacturing 49% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Paper manufacturing 49% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers hours 48% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Total value of shipments 47% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Furniture and related product manufacturing 47% [plot | correlate | graph]
...and  Labor > Transportation equipment manufacturing > Production workers (average per year) 47% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Value added 47% [plot | correlate | graph]
...and  Health > Total Physician Assistants 47% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Nonmetallic mineral product manufacturing 46% [plot | correlate | graph]
...and  Military > DOD Inactive Military Employees > Salaries & Wages 46% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Nonmetallic mineral product manufacturing 46% [plot | correlate | graph]
...and  Industry > Textile product mills > Total capital expenditures 46% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Food product manufacturing 46% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Food product manufacturing 46% [plot | correlate | graph]
...and  Health > Total State Health Care Spending 46% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Production workers wages 46% [plot | correlate | graph]
...and  Labor > Nonmetallic mineral product manufacturing > Production workers hours 46% [plot | correlate | graph]
...and  Labor > Nonmetallic mineral product manufacturing > Number of employees 45% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Truck transportation 45% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Truck transportation 45% [plot | correlate | graph]
...and  Health > Total Medicaid Spending, FY2004 45% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Furniture and related product manufacturing 45% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Furniture and related product manufacturing 45% [plot | correlate | graph]
...and  Industry > Food manufacturing > Value added 45% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Number of employees 45% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Annual payroll 45% [plot | correlate | graph]
...and  Labor > Printing & related support activities > Number of employees 44% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Truck transportation 44% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers (average per year) 44% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours 44% [plot | correlate | graph]
...and  Industry > Nonmetallic mineral product manufacturing > Production workers wages 44% [plot | correlate | graph]
Average: 55%

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
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