2016Unpublished venueRequires access

CORRELATION AND CONCORDANCE

Peter Sprent, Nigel C. Smeeton

Open publisher page 1 citations

Abstract

We often want measures that summarize the strength of relationships between variables. Correlation is a measure of the strength of association or dependence between two variables. In the parametric context, the Pearson product moment correlation coefficient estimates the degree of linear association between two variables. The coefficient takes values between −1 and +1. The extremes are attained only when points lie exactly on a straight line. The extreme −1 implies a negative slope, and +1 a positive slope. If one of the variables tends to be large when the other is large and small when the other is small, the correlation is positive. If large values of one variable are associated with small values of the other the correlation is negative. If the two variables are independent of each other, the value of the correlation is zero. A nonlinear relationship can also produce a correlation value close to zero. It is prudent to plot a scatter diagram before calculating any correlation coefficient.

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What this paper is about

We often want measures that summarize the strength of relationships between variables. Correlation is a measure of the strength of association or dependence between two variables. In the parametric context, the Pearson product moment correlation coefficient estimates the degree of linear association between two variables. The coefficient takes values between −1 and +1. The extremes are attained only when points lie exactly on a straight line. The extreme −1 implies a negative slope, and +1 a positive slope. If one of the variables tends to be large when the other is large and small when the other is small, the correlation is positive. If large values of one variable are associated with small values of the other the correlation is negative. If the two variables are independent of each other, the value of the correlation is zero. A nonlinear relationship can also produce a correlation value close to zero. It is prudent to plot a scatter diagram before calculating any correlation coefficient.

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Available abstract

We often want measures that summarize the strength of relationships between variables. Correlation is a measure of the strength of association or dependence between two variables. In the parametric context, the Pearson product moment correlation coefficient estimates the degree of linear association between two variables. The coefficient takes values between −1 and +1. The extremes are attained only when points lie exactly on a straight line. The extreme −1 implies a negative slope, and +1 a positive slope. If one of the variables tends to be large when the other is large and small when the other is small, the correlation is positive. If large values of one variable are associated with small values of the other the correlation is negative. If the two variables are independent of each other, the value of the correlation is zero. A nonlinear relationship can also produce a correlation value close to zero. It is prudent to plot a scatter diagram before calculating any correlation coefficient.

Key concepts: Concordance, Correlation, Mathematics, Biology, Genetics, Geometry

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