gammagirl Posted February 5, 2018 Share Posted February 5, 2018 How is a correlation coefficient of 0.999992 better than a correlation coefficient of 0.99996 even though both analyses resulted in the same molar absorptivity for the analyte using spectrophotometric analysis? Does 0.999992 result in a higher correlation coefficient than 0.99996? If so, why? Link to comment Share on other sites More sharing options...
hypervalent_iodine Posted February 5, 2018 Share Posted February 5, 2018 The R2 value is a measure of how well your data points fit the trend line. A higher correlation coefficient is better, as it tells you that your result is more precise (even if the numbers you calculate are the same). Link to comment Share on other sites More sharing options...
gammagirl Posted February 6, 2018 Author Share Posted February 6, 2018 Is the bottom line that both values are nearly perfect straight lines making the differences between the numbers negligible? Link to comment Share on other sites More sharing options...
John Cuthber Posted February 7, 2018 Share Posted February 7, 2018 Yes. And with R^2 values that high you are looking at slightly different noise Link to comment Share on other sites More sharing options...
gammagirl Posted February 7, 2018 Author Share Posted February 7, 2018 What do you mean by slightly different noise? Link to comment Share on other sites More sharing options...
AJKOER2 Posted March 31, 2018 Share Posted March 31, 2018 Perhaps a more meaning insight can be gathered from employing a non-parametric correlation measure. For example, look at the rank correlations, the so called Spearman Rank correlation statistic. If they are computed here to be 1.000 for both, there is no meaningful difference. One can also look up the approximate standard deviation measure for R2, and, I would guess, with even a very large sample size , no statistical meaningful difference here as well. Link to comment Share on other sites More sharing options...
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