The Student Room Group

PMCC vs Standard Deviation

Could someone help/explain this to me. The mark scheme didn't really help at all.

A student had 2 sets of bivariate data. He found the standard deviation and pmcc of each set.

Set A: pmcc = 0.9....sd = 1
Set B: pmcc = 1.......sd = 0.9

Why can the results for set A be correct but not both results for set B?
Original post by Fuenciado
Could someone help/explain this to me. The mark scheme didn't really help at all.

A student had 2 sets of bivariate data. He found the standard deviation and pmcc of each set.

Set A: pmcc = 0.9....sd = 1
Set B: pmcc = 1.......sd = 0.9

Why can the results for set A be correct but not both results for set B?


What's "sd" here? Standard deviation of what?
Reply 2
Original post by Fuenciado
Could someone help/explain this to me. The mark scheme didn't really help at all.

A student had 2 sets of bivariate data. He found the standard deviation and pmcc of each set.

Set A: pmcc = 0.9....sd = 1
Set B: pmcc = 1.......sd = 0.9

Why can the results for set A be correct but not both results for set B?


Do you have a link to the original question and to the mark scheme?
Reply 3
Original post by davros
Do you have a link to the original question and to the mark scheme?



Wasn't working as an image so I've done it as an attachment
Original post by Fuenciado
Wasn't working as an image so I've done it as an attachment


R sub s is spearman's rank, not standard deviation. Lower case sigma is standard deviation.
Reply 5
Original post by Protoxylic
R sub s is spearman's rank, not standard deviation. Lower case sigma is standard deviation.


Yeah I know, I didn't even notice that I'd called it the wrong thing.
I've done like 26 hours of stats in the last 3 days , I think my brain is broken.
So, now you know it's Spearman's Rank, do you know how to procede?
Reply 7
Original post by DFranklin
So, now you know it's Spearman's Rank, do you know how to procede?


Not really :s-smilie:
Original post by Fuenciado
Not really :s-smilie:


Pmcc is a measure of how good a fit a linear realationship is, with "1" (or "-1") being a perfect fit.

Spearmans is a measure of how good a fit a monotonic relationship is, with "1! (or "-1") being a perfect fit.

With that in mind, which of the two sets are giving you problems?
In case ghostwalker's post is a little too tech-speak:

If you plot the points on an X,Y scatter diagram, then PMCC = 1 means the points lie on a straght line, while SRCC = 1 means the points always go "up" as you increase X. (i.e. Y is an increasing function of X).

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