NationMaster - Correlations > Labor

	Variable	Strength
...and	Health > Probability of not reaching 60	71%	[plot \| correlate \| graph]
...and	Health > Age of women at first childbirth (inverse)	49%	[plot \| correlate \| graph]
...and	Education > Share of vocational tertiary qualifications awarded to females > First degree	47%	[plot \| correlate \| graph]
...and	Health > Heart disease deaths	45%	[plot \| correlate \| graph]
...and	People > Women > Life expectancy females as a % of males	44%	[plot \| correlate \| graph]
...and	Energy > Usage per person	43%	[plot \| correlate \| graph]
...and	Labor > Female decision makers	43%	[plot \| correlate \| graph]
...and	Education > Female teachers > Lower secondary	42%	[plot \| correlate \| graph]
...and	Labor > Working time to buy a car	41%	[plot \| correlate \| graph]
...and	Health > Duration of hospitalisation (inverse)	41%	[plot \| correlate \| graph]
...and	Health > Suicide rate > Young males	39%	[plot \| correlate \| graph]
...and	Health > Teenage pregnancy > Share	38%	[plot \| correlate \| graph]
...and	Crime > Suicide rates in ages 25-34	37%	[plot \| correlate \| graph]
...and	Health > Teen birth rate	36%	[plot \| correlate \| graph]
...and	Agriculture > Cereal production (inverse)	35%	[plot \| correlate \| graph]
...and	Agriculture > Agricultural growth (inverse)	35%	[plot \| correlate \| graph]
...and	Agriculture > Grains > Corn imports (inverse)	35%	[plot \| correlate \| graph]
...and	Religion > Islam > Percentage Muslim (inverse)	34%	[plot \| correlate \| graph]
...and	Crime > Believe in police efficiency	33%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 30-34	33%	[plot \| correlate \| graph]
...and	People > Women > Antenatal care coverage %	33%	[plot \| correlate \| graph]
...and	Labor > Working time to buy beef (inverse)	33%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 35-39	33%	[plot \| correlate \| graph]
...and	Crime > Bribe payers index	32%	[plot \| correlate \| graph]
...and	Lifestyle > Undesirable neighbours > People with AIDS (inverse)	32%	[plot \| correlate \| graph]
...and	Food > Wine consumption (inverse)	31%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 40-44	31%	[plot \| correlate \| graph]
...and	Education > Hours of instruction for pupils aged 13	31%	[plot \| correlate \| graph]
...and	Education > Literacy > Adults with at least moderate literacy > female	31%	[plot \| correlate \| graph]
...and	Education > Literacy > Adults with at least moderate literacy > male (inverse)	31%	[plot \| correlate \| graph]
...and	Education > Student attitude > Find school boring	31%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 45-49	30%	[plot \| correlate \| graph]
...and	People > Women > Adult literacy rate females as a % of males	30%	[plot \| correlate \| graph]
...and	Agriculture > Banana production	29%	[plot \| correlate \| graph]
...and	People > Teenage birth rate	29%	[plot \| correlate \| graph]
...and	Democracy > Bertelsmann Transformation Index>Political Transformation	29%	[plot \| correlate \| graph]
...and	People > Gender empowerment measure	28%	[plot \| correlate \| graph]
...and	Crime > Suicide rates in ages 15-24	28%	[plot \| correlate \| graph]
...and	Lifestyle > Happiness level > Not very or not at all happy	28%	[plot \| correlate \| graph]
...and	Economy > Male to female earnings (inverse)	28%	[plot \| correlate \| graph]
...and	Lifestyle > Happiness net (inverse)	28%	[plot \| correlate \| graph]
...and	Agriculture > Grains > Coarse grain imports (inverse)	28%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 25-29	28%	[plot \| correlate \| graph]
...and	Health > Nutrition > % of under-fives suffering from underweight severe (inverse)	27%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Both sexes aged 35-39	27%	[plot \| correlate \| graph]
...and	Education > Primary teacher age > Proportion aged 40-49 (inverse)	27%	[plot \| correlate \| graph]
...and	Economy > Gender income ratio	27%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 50-54	26%	[plot \| correlate \| graph]
...and	Education > Educational attainment > Tertiary	26%	[plot \| correlate \| graph]
...and	Health > Health care funding > Private per capita (inverse)	26%	[plot \| correlate \| graph]
	Average:	34%

About Correlations:

A correlation is a statistical measure of similarity between at least two given sets of data. NationMaster'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 countries, rather subsets of countries matched together.

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Detailed correlation information
Map & Graph: countries ranked

NOTES:

Outliers have been removed only where they are outside 3 standard deviations of the mean.
Only variable pairs where at least 15 countries 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: Female professional and technical workers (as % of total)

SOURCE: calculated on the basis of occupational data from ILO (International Labour Organization). 2002. Laboursta Database. February 2002

Correlations > Labor Statistics > Female professionals

Correlations between Labor > Female professionals ...

About Correlations:

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NOTES:

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