Charles Spearman was a British statistician
who invented a simple formula to measure the strength of linear
assosciation between two rankings, or how close the data fit to
a line. Spearman's Rank Correlation Coefficient can be denoted by
His equation is as follows;
The
means the sum of the differences squared, the n is the number of
objects you are ranking. Here is an example:
Car
Deven's Rank
Biff's Rank
Difference of Rank
Squared Difference
Corvette
4
5
1
1
Viper
1
1
0
0
Lamborghini
2
2
0
0
Porsche
5
3
2
4
Firebird
3
4
1
1
n=5 (number of objects ranked) (Sum of difference^2) (6)
Now we can substitute in our values from our equation above: = = .7
So =.7 Big deal, what does it mean? The value is basically on a scale of -1 to 1, the closer to -1 the less
alike the rankings are, the closer to 1, the more alike the rankings are. As you can see Deven and Biff's ranking of cars
were fairly close.
means the sum of the differences squared, the n is the number of
objects you are ranking. Here is an example:
= 
= .7
So 
=.7 Big deal, what does it mean? The 