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Correlations > Labor Statistics > Electrical equipment, appliance, & component manufacturing > Production workers hours

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Showing latest available data.

Correlations between Labor > Electrical equipment, appliance, & component manufacturing > Production workers hours ...

Variable Strength
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total cost of materials 68% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total value of shipments 66% [plot | correlate | graph]
...and  Labor > Electrical equipment, appliance, & component manufacturing > Production workers (average per year) 66% [plot | correlate | graph]
...and  Labor > Electrical equipment, appliance, & component manufacturing > Number of employees 62% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Electrical equipment and appliance manufacturing 61% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Electrical equipment and appliance manufacturing 61% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Value added 60% [plot | correlate | graph]
...and  Labor > Total Manufacturing > Number of employees 56% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Electrical equipment and appliance manufacturing 55% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Electrical equipment and appliance manufacturing 54% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Plastics and rubber products manufacturing 53% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Plastics and rubber products manufacturing 53% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Plastics and rubber products manufacturing 53% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Annual payroll 52% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total cost of materials 51% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Total capital expenditures 50% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total value of shipments 49% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Production workers (average per year) 49% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Total capital expenditures 47% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Value added 47% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Plastics and rubber products manufacturing 47% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Motor vehicle, body, trailer, and parts manufacturing 46% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Motor vehicle, body, trailer, and parts manufacturing 46% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Production workers wages 46% [plot | correlate | graph]
...and  Industry > Electrical equipment, appliance, & component manufacturing > Annual payroll 46% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Number of employees 45% [plot | correlate | graph]
...and  Labor > Machinery manufacturing > Production workers hours 45% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total cost of materials 44% [plot | correlate | graph]
...and  Industry > Total Manufacturing > Total capital expenditures 44% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total cost of materials 44% [plot | correlate | graph]
...and  Industry > Plastics & rubber products manufacturing > Annual payroll 44% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total cost of materials 44% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Plastics and rubber products manufacturing (per capita) 43% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Food product manufacturing 43% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Total value of shipments 42% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Truck transportation 41% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Production workers wages 41% [plot | correlate | graph]
...and  Industry > Food manufacturing > Annual payroll 41% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Fabricated metal product manufacturing 41% [plot | correlate | graph]
...and  Economy > GSP > Compensation of Employees > Paper manufacturing 40% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Total value of shipments 40% [plot | correlate | graph]
...and  Industry > Food manufacturing > Production workers wages 40% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Total value of shipments 39% [plot | correlate | graph]
...and  Education > Public Libraries > Circulation of Children's Materials 39% [plot | correlate | graph]
...and  Labor > Machinery manufacturing > Production workers (average per year) 38% [plot | correlate | graph]
...and  Industry > Machinery manufacturing > Value added 38% [plot | correlate | graph]
...and  Industry > Transportation equipment manufacturing > Production workers wages 37% [plot | correlate | graph]
...and  Labor > Paper manufacturing > Production workers hours 37% [plot | correlate | graph]
...and  Industry > Fabricated metal product manufacturing > Value added 37% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Machinery manufacturing 36% [plot | correlate | graph]
Average: 47%

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



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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