correlation - ορισμός. Τι είναι το correlation
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Τι (ποιος) είναι correlation - ορισμός

ANY STATISTICAL RELATIONSHIP, WHETHER CAUSAL OR NOT, BETWEEN TWO RANDOM VARIABLES OR BIVARIATE DATA
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  • [[Anscombe's quartet]]: four sets of data with the same correlation of 0.816
  • Several sets of (''x'', ''y'') points, with the [[Pearson correlation coefficient]] of ''x'' and ''y'' for each set. The correlation reflects the noisiness and direction of a linear relationship (top row), but not the slope of that relationship (middle), nor many aspects of nonlinear relationships (bottom). N.B.: the figure in the center has a slope of 0 but in that case, the correlation coefficient is undefined because the variance of ''Y'' is zero.
  • Example scatterplots of various datasets with various correlation coefficients.

correlation         
n. a correlation between
Correlated         
·Impf & ·p.p. of Correlate.
correlate         
['k?r?le?t, -r?-]
¦ verb have a relationship in which one thing affects or depends on another: most jobs do not directly correlate with GCSE subjects.
?establish a correlation between.
¦ noun each of two or more related or complementary things.
Origin
C17: back-form. from correlation and correlative.

Βικιπαίδεια

Correlation

In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics it usually refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve.

Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However, in general, the presence of a correlation is not sufficient to infer the presence of a causal relationship (i.e., correlation does not imply causation).

Formally, random variables are dependent if they do not satisfy a mathematical property of probabilistic independence. In informal parlance, correlation is synonymous with dependence. However, when used in a technical sense, correlation refers to any of several specific types of mathematical operations between the tested variables and their respective expected values. Essentially, correlation is the measure of how two or more variables are related to one another. There are several correlation coefficients, often denoted ρ {\displaystyle \rho } or r {\displaystyle r} , measuring the degree of correlation. The most common of these is the Pearson correlation coefficient, which is sensitive only to a linear relationship between two variables (which may be present even when one variable is a nonlinear function of the other). Other correlation coefficients – such as Spearman's rank correlation – have been developed to be more robust than Pearson's, that is, more sensitive to nonlinear relationships. Mutual information can also be applied to measure dependence between two variables.

Παραδείγματα από το σώμα κειμένου για correlation
1. He meant that the geographic correlation was stronger than the correlation between high test scores and high per–pupil expenditures.
2. Although nationwide statistics show a correlation between percentage of money spent statewide and standardized test scores, that correlation is not clear at the local district level.
3. Gone is the correlation between the means and the ends.
4. Interestingly the GDP correlation was weaker in the recent past.
5. He said: "Correlation is not necessarily the same as causation.