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Pearson correlation coefficient vs mutual information

Pearson correlation coefficient vs mutual information
  1. What is the difference between correlation and mutual information?
  2. Is mutual information a measure of correlation?
  3. What is the difference between Pearson correlation and correlation coefficient?
  4. How do you find the mutual information between two variables?

What is the difference between correlation and mutual information?

Correlation analysis provides a quantitative means of measuring the strength of a linear relationship between two vectors of data. Mutual information is essentially the measure of how much “knowledge” one can gain of a certain variable by knowing the value of another variable.

Is mutual information a measure of correlation?

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures.

What is the difference between Pearson correlation and correlation coefficient?

Correlation coefficients describe the strength and direction of an association between variables. A Pearson correlation is a measure of a linear association between 2 normally distributed random variables.

How do you find the mutual information between two variables?

The mutual information between two random variables X and Y can be stated formally as follows: I(X ; Y) = H(X) – H(X | Y)

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