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Correlations > Labor Statistics > Transportation equipment manufacturing > Number of employees

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Showing latest available data.

Correlations between Labor > Transportation equipment manufacturing > Number of employees ...

Variable Strength
...and  Industry > Transportation equipment manufacturing > Annual payroll 96% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Value added 90% [plot | correlate | graph]
...and  Labor > Transportation equipment manufacturing > Production workers hours 90% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Production workers wages 88% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total value of shipments 86% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total capital expenditures 79% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total cost of materials 78% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Motor vehicle, body, trailer, and parts manufacturing 71% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Motor vehicle, body, trailer, and parts manufacturing 71% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Production workers wages 67% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Motor vehicle, body, trailer, and parts manufacturing 66% [plot | correlate | graph]
...and  Labor > Plastics & rubber products manufacturing > Production workers (average per year) 64% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Annual payroll 63% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Motor vehicle, body, trailer, and parts manufacturing (per capita) 62% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Production workers wages 62% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Motor vehicle, body, trailer, and parts manufacturing (per $ GDP) 60% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Furniture and related product manufacturing 59% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Annual payroll (per capita) 58% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total capital expenditures 58% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Annual payroll (per $ GDP) 58% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Value added 58% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Production workers wages (per $ GDP) 57% [plot | correlate | graph]
...and  Labor > Fabricated metal product manufacturing > Production workers hours 57% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours 57% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers (average per year) 57% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total value of shipments 57% [plot | correlate | graph]
...and  Labor > Transportation equipment manufacturing > Number of employees (per capita) 57% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials 56% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Plastics and rubber products manufacturing 56% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Value added 55% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total value of shipments 55% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Value added 55% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total value of shipments 54% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Annual payroll 54% [plot | correlate | graph]
...and  Labor > Machinery manufacturing > Number of employees 54% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Primary metal manufacturing 54% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Primary metal manufacturing 54% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Primary metal manufacturing 54% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Value added (per $ GDP) 54% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total value of shipments 54% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total cost of materials 53% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total capital expenditures 53% [plot | correlate | graph]
...and  Labor > Transportation equipment manufacturing > Production workers hours (per capita) 53% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total capital expenditures 53% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total cost of materials 53% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total cost of materials 52% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total value of shipments (per $ GDP) 52% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Annual payroll 52% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Production workers wages 51% [plot | correlate | graph]
...and  Labor > Machinery manufacturing > Production workers hours 51% [plot | correlate | graph]
Average: 61%

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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