# A report on Correlation

Any statistical relationship, whether causal or not, between two random variables or bivariate data.

- Correlation19 related topics with Alpha

## Pearson correlation coefficient

4 linksIn statistics, the Pearson correlation coefficient (PCC, pronounced ) ― also known as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC), the bivariate correlation, or colloquially simply as the correlation coefficient ― is a measure of linear correlation between two sets of data.

## Statistics

2 linksDiscipline that concerns the collection, organization, analysis, interpretation, and presentation of data.

Discipline that concerns the collection, organization, analysis, interpretation, and presentation of data.

These inferences may take the form of answering yes/no questions about the data (hypothesis testing), estimating numerical characteristics of the data (estimation), describing associations within the data (correlation), and modeling relationships within the data (for example, using regression analysis).

## Causality

2 linksInfluence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object ( an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause.

Influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object ( an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause.

Alternative methods of structure learning search through the many possible causal structures among the variables, and remove ones which are strongly incompatible with the observed correlations.

## Covariance

1 linksMeasure of the joint variability of two random variables.

Measure of the joint variability of two random variables.

The sign of the covariance therefore shows the tendency in the linear relationship between the variables.

## Francis Galton

1 linksEnglish Victorian era polymath: a statistician, sociologist, psychologist, anthropologist, tropical explorer, geographer, inventor, meteorologist, proto-geneticist, psychometrician and a proponent of social Darwinism, eugenics, and scientific racism.

English Victorian era polymath: a statistician, sociologist, psychologist, anthropologist, tropical explorer, geographer, inventor, meteorologist, proto-geneticist, psychometrician and a proponent of social Darwinism, eugenics, and scientific racism.

He also created the statistical concept of correlation and widely promoted regression toward the mean.

## Karl Pearson

2 linksEnglish mathematician and biostatistician.

English mathematician and biostatistician.

These techniques, which are widely used today for statistical analysis, include the chi-squared test, standard deviation, and correlation and regression coefficients.

## Correlation does not imply causation

1 linksThe phrase "correlation does not imply causation" refers to the inability to legitimately deduce a cause-and-effect relationship between two events or variables solely on the basis of an observed association or correlation between them.

## Correlation coefficient

0 linksA correlation coefficient is a numerical measure of some type of correlation, meaning a statistical relationship between two variables.

## Multivariate normal distribution

0 linksGeneralization of the one-dimensional normal distribution to higher dimensions.

Generalization of the one-dimensional normal distribution to higher dimensions.

The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables each of which clusters around a mean value.

## Odds ratio

0 linksAn odds ratio (OR) is a statistic that quantifies the strength of the association between two events, A and B. The odds ratio is defined as the ratio of the odds of A in the presence of B and the odds of A in the absence of B, or equivalently (due to symmetry), the ratio of the odds of B in the presence of A and the odds of B in the absence of A. Two events are independent if and only if the OR equals 1, i.e., the odds of one event are the same in either the presence or absence of the other event.