Correlation

From WikiMD's Food, Medicine & Wellness Encyclopedia

Correlation is a statistical measure that describes the degree to which two variables move in relation to each other. In the field of statistics, correlation is used to measure the strength and direction of the relationship between two variables.

Definition[edit | edit source]

Correlation is defined as the statistical relationship between two or more variables that change together, though not necessarily at the same rate. The correlation coefficient is a measure of the strength of this relationship. It is represented by the letter 'r' and can range from -1 to 1.

Types of Correlation[edit | edit source]

There are three types of correlation: positive, negative, and zero correlation.

  • Positive Correlation: When the values of both variables increase or decrease together, the correlation is said to be positive.
  • Negative Correlation: When the value of one variable increases while the other decreases, the correlation is said to be negative.
  • Zero Correlation: When there is no relationship between the variables, the correlation is said to be zero.

Correlation vs Causation[edit | edit source]

It is important to note that correlation does not imply causation. Just because two variables correlate does not mean that one causes the other to occur. They may be related due to a third, unseen factor, known as a confounding variable.

Correlation in Medical Research[edit | edit source]

In medical research, correlation is used to determine if a relationship exists between two health-related variables, for example, smoking and lung cancer. This can help identify risk factors for diseases and guide public health interventions.

Calculating Correlation[edit | edit source]

The correlation between two variables can be calculated using the Pearson correlation coefficient formula. This formula takes into account the standard deviation and mean of both variables.

Limitations of Correlation[edit | edit source]

While correlation can indicate a possible relationship between two variables, it does not prove a cause-and-effect relationship. Correlation also cannot measure non-linear relationships, only linear ones.

See Also[edit | edit source]

Correlation Resources
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Contributors: Prab R. Tumpati, MD