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Spearman coefficient of
correlation
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 1
Definition
Spearman correlation coefficient
• The Spearman’s rank coefficient of correlation is a
nonparametric measure of rank correlation (statistical
dependence of ranking between two variables).
• Named after Charles Spearman, it is often denoted by
the Greek letter ‘ρ’ (rho) and is primarily used for data
analysis.
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 2
3. It measures the strength and
direction of the association between
two ranked variables.
4. But before we talk about the Spearman
correlation coefficient, it is important to understand
Pearson’s correlation first. A Pearson correlation is a
statistical measure of the strength of a linear
relationship between paired data.
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 3
5. For the calculation and
significance testing of the
ranking variable, it requires the
following data assumption to
hold true:
• Interval or ratio level
• Linearly related
• Bivariant distributed
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 4
6. IF YOUR DATA DOESN’T MEET THE ABOVE ASSUMPTIONS,
THEN YOU WOULD NEED SPEARMAN’S COEFFICIENT.
7. IT IS NECESSARY TO KNOW WHAT MONOTONIC FUNCTION
IS TO UNDERSTAND SPEARMAN CORRELATION COEFFICIENT. A
MONOTONIC FUNCTION IS ONE THAT EITHER NEVER
DECREASES OR NEVER INCREASES AS IT IS AN INDEPENDENT
VARIABLE INCREASE. A MONOTONIC FUNCTION CAN BE
EXPLAINED USING THE IMAGE BELOW:
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 5
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 6
The image explains three concepts in monotonic function:
a. Monotonically increasing: When the ‘x’ variable increases and
the ‘y’ variable never decreases.
b. Monotonically decreasing: When the ‘x’ variable increases but
the ‘y’ variable never increases
c. Not monotonic: When the ‘x’ variable increases and the ‘y’
variable sometimes increases and sometimes decreases.
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 7
Monotonic relation is less restrictive when compared to a linear relationship that is
used in Pearson’s coefficient. Although monotonicity is not the ultimate requirement
for Spearman correlation coefficient, it will not be meaningful to pursue Spearman’s
correlation without actually determining the strength and direction of a monotonic
relationship if it was already known that the relationship between the variable is non-
monotonic.
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 8
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 9
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 10
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 11
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 12
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 13
Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 14

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Unit i bp801 t k spearman coefficient of correlation24022022

  • 1. Spearman coefficient of correlation Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 1
  • 2. Definition Spearman correlation coefficient • The Spearman’s rank coefficient of correlation is a nonparametric measure of rank correlation (statistical dependence of ranking between two variables). • Named after Charles Spearman, it is often denoted by the Greek letter ‘ρ’ (rho) and is primarily used for data analysis. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 2
  • 3. 3. It measures the strength and direction of the association between two ranked variables. 4. But before we talk about the Spearman correlation coefficient, it is important to understand Pearson’s correlation first. A Pearson correlation is a statistical measure of the strength of a linear relationship between paired data. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 3
  • 4. 5. For the calculation and significance testing of the ranking variable, it requires the following data assumption to hold true: • Interval or ratio level • Linearly related • Bivariant distributed Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 4
  • 5. 6. IF YOUR DATA DOESN’T MEET THE ABOVE ASSUMPTIONS, THEN YOU WOULD NEED SPEARMAN’S COEFFICIENT. 7. IT IS NECESSARY TO KNOW WHAT MONOTONIC FUNCTION IS TO UNDERSTAND SPEARMAN CORRELATION COEFFICIENT. A MONOTONIC FUNCTION IS ONE THAT EITHER NEVER DECREASES OR NEVER INCREASES AS IT IS AN INDEPENDENT VARIABLE INCREASE. A MONOTONIC FUNCTION CAN BE EXPLAINED USING THE IMAGE BELOW: Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 5
  • 6. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 6
  • 7. The image explains three concepts in monotonic function: a. Monotonically increasing: When the ‘x’ variable increases and the ‘y’ variable never decreases. b. Monotonically decreasing: When the ‘x’ variable increases but the ‘y’ variable never increases c. Not monotonic: When the ‘x’ variable increases and the ‘y’ variable sometimes increases and sometimes decreases. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 7
  • 8. Monotonic relation is less restrictive when compared to a linear relationship that is used in Pearson’s coefficient. Although monotonicity is not the ultimate requirement for Spearman correlation coefficient, it will not be meaningful to pursue Spearman’s correlation without actually determining the strength and direction of a monotonic relationship if it was already known that the relationship between the variable is non- monotonic. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 8
  • 9. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 9
  • 10. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 10
  • 11. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 11
  • 12. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 12
  • 13. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 13
  • 14. Dr. Ashish Suttee, M.Pharm., MBAHCS., PGD Stat., Ph.D. 14