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I have been told to take a closer look at: http://www.quantpsy.org/corrtest/corrtest.htm but how exactly does this work?

E.g. Given two groups of data A and B, each with one explanatory variable and one response variable, each with e.g. n=20 data points, I can calculate Spearman's Correlation Coefficient SCC yielding SCC = 0.9 in group A and in group B I get SCC=-0.9.

From the above, it is obvious that in group A the data is well correlated with a slope >0 and in group B also well correlated, but with a slope <0, so definitely a difference - Right?

Now to the real question: The SCC quantifies in a non-parametric way how well correlated the explanatory and response variables are, but I am not sure I understand how it works with testing the difference between two correlations? I am thinking that testing SCC=0.3 and SCC=0.8 should not yield anything, since basically one correlation is crappy and the other is sort of ok? But the link yields p=0.02

I have been told to take a closer look at: http://www.quantpsy.org/corrtest/corrtest.htm but how exactly does this work?

E.g. Given two groups of data A and B, each with one explanatory variable and one response variable, each with e.g. n=20 data points, I can calculate Spearman's Correlation Coefficient SCC yielding SCC = 0.9 in group A and in group B I get SCC=-0.9.

From the above, it is obvious that in group A the data is well correlated with a slope >0 and in group B also well correlated, but with a slope <0, so definitely a difference - Right?

Now to the real question: The SCC quantifies in a non-parametric way how well correlated the explanatory and response variables are, but I am not sure I understand how it works with testing the difference between two correlations? I am thinking that testing SCC=0.3 and SCC=0.8 should not yield anything, since basically one correlation is rather weak and the other is sort of ok? But the link yields p=0.02

I have been told to take a closer look at: http://www.quantpsy.org/corrtest/corrtest.htm but how exactly does this work?

E.g. Given two groups of data A and B, each with one explanatory variable and one response variable, each with e.g. n=20 data points, I can calculate Spearman's Correlation Coefficient SCC yielding SCC = 0.9 in group A and in group B I get SCC=-0.9.

From the above, it is obvious that in group A the data is well correlated with a slope >0 and in group B also well correlated, but with a slope <0, so definitely a difference - Right?

Now to the real question: The SCC quantifies in a non-parametric way how well correlated the explanatory and response variables are, but I am not sure I understand how it works with testing the difference between two correlations? I am thinking that testing SCC=0.3 and SCC=0.8 should not yield anything, since basically one correlation is crappy and the other is sort of ok? But the link yields p=0.02

Cheers!

I have been told to take a closer look at: http://www.quantpsy.org/corrtest/corrtest.htm but how exactly does this work?

E.g. Given two groups of data A and B, each with one explanatory variable and one response variable, each with e.g. n=20 data points, I can calculate Spearman's Correlation Coefficient SCC yielding SCC = 0.9 in group A and in group B I get SCC=-0.9.

From the above, it is obvious that in group A the data is well correlated with a slope >0 and in group B also well correlated, but with a slope <0, so definitely a difference - Right?

Now to the real question: The SCC quantifies in a non-parametric way how well correlated the explanatory and response variables are, but I am not sure I understand how it works with testing the difference between two correlations? I am thinking that testing SCC=0.3 and SCC=0.8 should not yield anything, since basically one correlation is crappy and the other is sort of ok? But the link yields p=0.02

I have been told to take a closer look at: http://www.quantpsy.org/corrtest/corrtest.htm but how exactly does this work?

E.g. Given two groups of data A and B, each with one explanatory variable and one response variable, each with e.g. n=20 data points, I can calculate Spearman's Correlation Coefficient SCC yielding SCC = 0.9 in group A and in group B I get SCC=-0.9.

From the above, it is obvious that in group A the data is well correlated with a slope >0 and in group B also well correlated, but with a slope <0 - Right?

Now to the real question: The SCC quantifies in a non-parametric way how well correlated the explanatory and response variables are, but I am not sure I understand how it works with testing the difference between two correlations? I am thinking that testing SCC=0.3 and SCC=0.8 should not yield anything, since basically one correlation is crappy and the other is sort of ok? But the link yields p=0.2

Cheers!

I have been told to take a closer look at: http://www.quantpsy.org/corrtest/corrtest.htm but how exactly does this work?

E.g. Given two groups of data A and B, each with one explanatory variable and one response variable, each with e.g. n=20 data points, I can calculate Spearman's Correlation Coefficient SCC yielding SCC = 0.9 in group A and in group B I get SCC=-0.9.

From the above, it is obvious that in group A the data is well correlated with a slope >0 and in group B also well correlated, but with a slope <0, so definitely a difference - Right?

Now to the real question: The SCC quantifies in a non-parametric way how well correlated the explanatory and response variables are, but I am not sure I understand how it works with testing the difference between two correlations? I am thinking that testing SCC=0.3 and SCC=0.8 should not yield anything, since basically one correlation is crappy and the other is sort of ok? But the link yields p=0.02

Cheers!