Standard deviation line

Plot of the standard deviation line (SD line), dashed, and the regression line, solid, for a scatter diagram of 20 points.

In statistics, the standard deviation line (or SD line) marks points on a scatter plot that are an equal number of standard deviations away from the average in each dimension. For example, in a 2-dimensional scatter diagram with variables x {\displaystyle x} and y {\displaystyle y} , points that are 1 standard deviation away from the mean of x {\displaystyle x} and also 1 standard deviation away from the mean of y {\displaystyle y} are on the SD line.[1] The SD line is a useful visual tool since points in a scatter diagram tend to cluster around it,[1] more or less tightly depending on their correlation.

Properties

Relation to regression line

The SD line goes through the point of averages and has a slope of σ y σ x {\displaystyle {\frac {\sigma _{y}}{\sigma _{x}}}} when the correlation between x {\displaystyle x} and y {\displaystyle y} is positive, and σ y σ x {\displaystyle -{\frac {\sigma _{y}}{\sigma _{x}}}} when the correlation is negative.[1][2] Unlike the regression line, the SD line does not take into account the relationship between x {\displaystyle x} and y {\displaystyle y} .[3] The slope of the SD line is related to that of the regression line by a = r σ y σ x {\displaystyle a=r{\frac {\sigma _{y}}{\sigma _{x}}}} where a {\displaystyle a} is the slope of the regression line, r {\displaystyle r} is the correlation coefficient, and σ y σ x {\displaystyle {\frac {\sigma _{y}}{\sigma _{x}}}} is the magnitude of the slope of the SD line.[2]

Typical distance of points to SD line

The root mean square vertical distance of points from the SD line is 2 ( 1 | r | ) × σ y {\displaystyle {\sqrt {2(1-|r|)}}\times \sigma _{y}} .[1] This gives an idea of the spread of points around the SD line.

  1. ^ a b c d Freedman, David (1998). Statistics. Robert Pisani, Roger Purves (3rd ed.). New York: W.W. Norton. ISBN 0-393-97083-3. OCLC 36922529.
  2. ^ a b Stark. "Regression". www.stat.berkeley.edu. Retrieved 2022-11-12.
  3. ^ Cochran. "Regression". www.stat.ucla.edu. Retrieved 2022-11-12.