## Spearman

### proposed that general intelligence (g) is linked to many clusters that can be analyzed by factor analysis

Spearman’s rank correlation coefficient is a statistical method used to measure the strength and direction of the association between two variables. It is a non-parametric method, which means that it can be used with data that is not normally distributed.

The procedure involves ranking the data for each variable from lowest to highest and assigning a rank value. Then, the difference between the ranks for each pair of observations for the two variables is calculated. The formula for calculating the correlation coefficient is:

rs=1-(6Σd^2)/(n^3-n)

where rs is the Spearman rank correlation coefficient, d is the difference between the ranks for each pair of observations, and n is the sample size.

A value of rs between -1 and 1 indicates the strength and direction of the relationship between the two variables. If rs is close to 1, it suggests that there is a strong positive relationship between the two variables, while if rs is close to -1, it suggests that there is a strong negative relationship between the two variables. If rs is close to 0, it suggests that there is no clear relationship between the two variables.

Overall, Spearman’s rank correlation coefficient is a useful tool for analyzing data that does not meet the assumptions of parametric methods and can provide insights into the relationship between two variables.

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