In article [EMAIL PROTECTED] (Donald Burrill) wrote:
> Sounds like a prediction or calibration kind of problem. As Joe Ward
> pointed out, raw regression coefficients, and standard errors of
> measurement, are more stable than correlation coefficients.
Yes, that's right. Regression will be imp
Thanks for the replys so far. I've given more information below.
In article [EMAIL PROTECTED] (Donald Burrill) wrote:
> To whom, for what purpose(s) ? The "several bivariate associations"
> part rather suggests that you'll want to be making comparisons,
> implicitly if not explicitly; and eve
I'm considering reporting Pearson's correlation coefficient with a
confidence interval for several bivariate associations. As bivariate
normality is assumed under the computation of the confidence interval,
I have two questions.
1. What is a good way to examine the assumption of bivariate norma
