Re: Difference Fit vs. Correlation
- To: mathgroup at smc.vnet.net
- Subject: [mg96815] Re: Difference Fit vs. Correlation
- From: Bill Rowe <readnews at sbcglobal.net>
- Date: Wed, 25 Feb 2009 04:06:41 -0500 (EST)
On 2/24/09 at 5:48 AM, clausenator at gmail.com (Claus) wrote:
>Hi, in the code below, using Correlation I get 0.501338, using Fit I
>get 0.514093. How come?
<snip>
>In[60]:= lm = LinearModelFit[GaltonDat, {1, x}, x]
>In[62]:= lm["BestFit"]
>Out[62]= 33.8866 + 0.514093 x
>In[63]:= r2 = Correlation[GaltonX, GaltonY]
>Out[63]= 0.501338
You seem to expect the slope of the best fit line to have the
same value as the correlation between x and y. These are two
separate things and will never have the same value with real data.
The slope of the best fit line is given by
Covariance[x,y]/Variance[y]
The correlation between x and y (Pearson's correlation) is given by
Covariance[x,y]/Sqrt[ Variance[x] Variance[y] ]
The only case where the slope and correlation have the same
value is the trivial case where x = y and there is no error
term, i.e., perfect correlation with a slope of 1.