NationMaster - Correlations > Labor > Working time to buy beef

	Variable	Strength
...and	Agriculture > Tractor concentration	67%	[plot \| correlate \| graph]
...and	Agriculture > Workers per hectare	58%	[plot \| correlate \| graph]
...and	Health > Tuberculosis cases > Per 100,000	54%	[plot \| correlate \| graph]
...and	Democracy > Female candidacy	51%	[plot \| correlate \| graph]
...and	Health > Stomach cancer deaths	51%	[plot \| correlate \| graph]
...and	Education > Student attitude > Find school boring (inverse)	48%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Men aged 30-34	45%	[plot \| correlate \| graph]
...and	Health > Heart disease deaths (inverse)	45%	[plot \| correlate \| graph]
...and	Labor > Female decision makers (inverse)	44%	[plot \| correlate \| graph]
...and	Education > Young longtext readers (inverse)	44%	[plot \| correlate \| graph]
...and	Health > Obesity (inverse)	42%	[plot \| correlate \| graph]
...and	People > Gender empowerment (inverse)	40%	[plot \| correlate \| graph]
...and	People > Gender empowerment measure (inverse)	40%	[plot \| correlate \| graph]
...and	Education > Share of university qualifications awarded to females (inverse)	40%	[plot \| correlate \| graph]
...and	Education > Share of university qualifications awarded to females > First degree (inverse)	40%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Men aged 45-49	37%	[plot \| correlate \| graph]
...and	Environment > Pollution > Nitrogen Oxides per capita (inverse)	36%	[plot \| correlate \| graph]
...and	Education > School life expectancy > Female (inverse)	35%	[plot \| correlate \| graph]
...and	Economy > Comparative price levels	35%	[plot \| correlate \| graph]
...and	Food > Fruit juice consumption (inverse)	34%	[plot \| correlate \| graph]
...and	Health > Suicide rate > Gender ratio (inverse)	34%	[plot \| correlate \| graph]
...and	Lifestyle > Confidence in social institutions > Press	34%	[plot \| correlate \| graph]
...and	Lifestyle > Political action > Joined a boycott (inverse)	34%	[plot \| correlate \| graph]
...and	Health > Hospital beds	34%	[plot \| correlate \| graph]
...and	Geography > Population density	33%	[plot \| correlate \| graph]
...and	Economy > Gender income ratio (inverse)	33%	[plot \| correlate \| graph]
...and	Environment > Carbon efficiency (inverse)	33%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Men aged 65 plus	33%	[plot \| correlate \| graph]
...and	Labor > Female professionals (inverse)	33%	[plot \| correlate \| graph]
...and	Labor > Female doctors (inverse)	32%	[plot \| correlate \| graph]
...and	Health > Life expectancy > Healthy years	32%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Men aged 25-29	32%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Men aged 35-39	32%	[plot \| correlate \| graph]
...and	Education > Tertiary enrollment (inverse)	31%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Both sexes aged 65 plus	31%	[plot \| correlate \| graph]
...and	Health > Suicide rate > Middle aged	31%	[plot \| correlate \| graph]
...and	Economy > Trade with US > US imports of photographic and optical equipment	31%	[plot \| correlate \| graph]
...and	Education > School life expectancy > Total (inverse)	31%	[plot \| correlate \| graph]
...and	Health > Life expectancy > Male healthy years	30%	[plot \| correlate \| graph]
...and	Education > Expected duration of education for females (inverse)	29%	[plot \| correlate \| graph]
...and	People > Female population > Age 15-19 > % of the total (inverse)	29%	[plot \| correlate \| graph]
...and	Lifestyle > Members of voluntary organisations > Charity (inverse)	29%	[plot \| correlate \| graph]
...and	People > Total population > Age 15-19 > % of the total (inverse)	29%	[plot \| correlate \| graph]
...and	Environment > Wildness (inverse)	29%	[plot \| correlate \| graph]
...and	Health > Life expectancy > Female healthy years	28%	[plot \| correlate \| graph]
...and	People > Male population > Age 15-19 > % of the total (inverse)	28%	[plot \| correlate \| graph]
...and	Health > Circulatory disease deaths (inverse)	28%	[plot \| correlate \| graph]
...and	Labor > Economic activity > Women aged 65 plus	27%	[plot \| correlate \| graph]
...and	Economy > Trade with US > US exports of soybeans	27%	[plot \| correlate \| graph]
...and	Environment > Non-wildness	27%	[plot \| correlate \| graph]
	Average:	36%

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: Number of minutes worked by average worker to buy one kilo of beef. The comparison of income levels only becomes meaningful if the cost of buying the necessities and luxuries of life is also considered.

SOURCE: International Metalworkers' Federation, The Purchasing Power of Working Time 2002: An International Comparison of Average Net Hourly Earnings 2001 (International Metalworkers' Federation, Geneva, 2002)

Correlations > Labor Statistics > Working time to buy beef

Correlations between Labor > Working time to buy beef ...

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