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1. Correlation evaluation

Thanks hismoth. How do I then use this stat? In my case, I have something like 300 independent variables, all with an n=66, and with confidence intervals varying between 0.0015 and 0.50. So could I reasonably say that correlations above (say) 0.5 with a confidence interval of below 0.01 are...
2. Correlation evaluation

Is there a single statistic which can reflect the different importance between similar correlations, say 0.7, based on different sample sizes such as n=10 and n=1,000?
3. To assess meaningfulness between an independent variable and a dependent one, is just the p value alone adequate and/or the correlation?

Thanks hismith; will do
4. To assess meaningfulness between an independent variable and a dependent one, is just the p value alone adequate and/or the correlation?

Thanks to you all for your guidance. I think this confirms my way of progressing in using the results of my linear regression usage. I am relating many lifestyle independent variables against somewhat fewer (but still a lot) of independent biomarkers. For some, such as blood pressure and body...
5. To assess meaningfulness between an independent variable and a dependent one, is just the p value alone adequate and/or the correlation?

To decide whether there is a probable meaningful relationship between dependent/independent variables, is it best to use just the t test (at, say, 5%; anything less than this meaning it is unlikely for the relationship to happen by chance and so is probably meaningful); or look at the variance...