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Correlations > Labor Statistics > Transportation equipment manufacturing > Production workers hours

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Correlations between Labor > Transportation equipment manufacturing > Production workers hours ...

Variable Strength
...and  Industry > Transportation equipment manufacturing > Production workers wages 95% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total value of shipments 93% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Value added 91% [plot | correlate | graph]
...and  Labor > Transportation equipment manufacturing > Number of employees 90% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Annual payroll 89% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total cost of materials 88% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Motor vehicle, body, trailer, and parts manufacturing 85% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Motor vehicle, body, trailer, and parts manufacturing 85% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total capital expenditures 84% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Motor vehicle, body, trailer, and parts manufacturing 78% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Primary metal manufacturing 76% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Primary metal manufacturing 76% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Primary metal manufacturing 72% [plot | correlate | graph]
...and  Labor > Plastics & rubber products manufacturing > Production workers (average per year) 67% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Production workers wages 67% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Annual payroll 67% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers hours 67% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total cost of materials 67% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Production workers wages 66% [plot | correlate | graph]
...and  Labor > Primary metal manufacturing > Production workers (average per year) 66% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Plastics and rubber products manufacturing 65% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Production workers wages 65% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials 65% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total value of shipments 65% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total value of shipments 64% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total capital expenditures 64% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total cost of materials 63% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Value added 63% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Total capital expenditures 62% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total value of shipments 61% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total capital expenditures 61% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers hours 59% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Value added 59% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Value added 58% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Plastics and rubber products manufacturing 56% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Plastics and rubber products manufacturing 56% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Fabricated metal product manufacturing 56% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Production workers (average per year) 56% [plot | correlate | graph]
...and  Labor > Fabricated metal product manufacturing > Number of employees 55% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Primary metal manufacturing 54% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total value of shipments 54% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total capital expenditures 54% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Furniture and related product manufacturing 54% [plot | correlate | graph]
...and  Labor > Transportation equipment manufacturing > Production workers hours (per capita) 54% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Motor vehicle, body, trailer, and parts manufacturing 54% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Production workers wages 53% [plot | correlate | graph]
...and  Labor > Fabricated metal product manufacturing > Production workers hours 53% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Value added 53% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total cost of materials 52% [plot | correlate | graph]
...and  Industry > Primary metal manufacturing > Annual payroll 52% [plot | correlate | graph]
Average: 66%

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 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.

SOURCE: Annual Survey of Manufactures, 2004

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