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Correlations > Industry Statistics > Apparel manufacturing > Total cost of materials (per $ GDP)

DEFINITION: This term refers to direct charges actually paid or payable for items consumed or put into production during the year, including freight charges and other direct charges incurred by the establishment in acquiring these materials. It includes the cost of materials or fuel consumed, whether purchased by the individual establishment from other companies, transferred to it from other establishments of the same company, or withdrawn from inventory during the year. Per $ GDP figures expressed per 1,000 $ gross domestic product.
VIEW DATA:   Totals   Per $ GDP  
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Showing latest available data.

Correlations between Industry > Apparel manufacturing > Total cost of materials (per $ GDP) ...

Variable Strength
...and  Industry > Apparel manufacturing > Value added (per $ GDP) 91% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total value of shipments (per $ GDP) 90% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll (per $ GDP) 89% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Apparel manufacturing (per $ GDP) 82% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Apparel manufacturing (per $ GDP) 82% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers hours (per capita) 82% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll (per capita) 80% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Apparel manufacturing (per capita) 70% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Apparel manufacturing (per capita) 70% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Production workers wages (per $ GDP) 68% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Apparel manufacturing (per $ GDP) 62% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Apparel manufacturing (per capita) 52% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Number of employees (per capita) 50% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total capital expenditures (per $ GDP) 50% [plot | correlate | graph]
...and  Labor > Beverage & tobacco product manufacturing > Production workers (average per year) (per capita) 48% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers hours 46% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Value added 45% [plot | correlate | graph]
...and  Labor > Apparel manufacturing > Production workers (average per year) (per capita) 44% [plot | correlate | graph]
...and  Industry > Textile product mills > Value added 44% [plot | correlate | graph]
...and  Industry > Textile product mills > Total value of shipments 43% [plot | correlate | graph]
...and  Health > Medicare Beneficiaries Below 150% FPL 42% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Production workers wages 40% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers (average per year) 40% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total value of shipments 40% [plot | correlate | graph]
...and  Education > Percent of People Who Have Completed High School (Including Equivalency) (inverse) 39% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Total cost of materials 39% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Textile and textile product mills 38% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Textile and textile product mills 38% [plot | correlate | graph]
...and  Industry > Textile product mills > Annual payroll 38% [plot | correlate | graph]
...and  Industry > Textile product mills > Total cost of materials 38% [plot | correlate | graph]
...and  Health > Diabetes per 100 Adults 38% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Annual payroll (per capita) 38% [plot | correlate | graph]
...and  Industry > Textile product mills > Value added (per $ GDP) 37% [plot | correlate | graph]
...and  Industry > Beverage & tobacco product manufacturing > Annual payroll (per $ GDP) 37% [plot | correlate | graph]
...and  Health > Hospice Services 36% [plot | correlate | graph]
...and  Industry > Apparel manufacturing > Annual payroll 36% [plot | correlate | graph]
...and  Health > SSI Beneficiaries as % of Population 36% [plot | correlate | graph]
...and  Labor > Textile product mills > Number of employees 36% [plot | correlate | graph]
...and  Industry > Textile product mills > Production workers wages 35% [plot | correlate | graph]
...and  Health > Diabetes 35% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Total cost of materials 35% [plot | correlate | graph]
...and  Health > Percent of Women with High Blood Pressure 35% [plot | correlate | graph]
...and  Health > High blood pressure 34% [plot | correlate | graph]
...and  Industry > Furniture & related product manufacturing > Production workers wages 34% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Production workers hours 34% [plot | correlate | graph]
...and  Economy > GSP > Nominal GSP > Textile and textile product mills (per $ GDP) 34% [plot | correlate | graph]
...and  Economy > GSP > Real GSP > Textile and textile product mills (per $ GDP) 34% [plot | correlate | graph]
...and  Economy > GSP > Gross Operating Surplus > Textile and textile product mills 33% [plot | correlate | graph]
...and  Industry > Textile product mills > Annual payroll (per $ GDP) 33% [plot | correlate | graph]
...and  Labor > Furniture & related product manufacturing > Number of employees 32% [plot | correlate | graph]
Average: 48%

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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