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Can a low correlation be significant?
Do not confuse statistical significance with practical importance. They are quite different issues. However, a weak correlation can be statistically significant, if the sample size is large enough.
Is correlation r affected by extreme values?
Correlation describes linear relationships. Correlation does not describe curve relationships between variables, no matter how strong the relationship is. The correlation coefficient is based on means and standard deviations, so it is not robust to outliers; it is strongly affected by extreme observations.
Is regression affected by extreme values?
With respect to regression, outliers are influential only if they have a big effect on the regression equation. Sometimes, outliers do not have big effects. For example, when the data set is very large, a single outlier may not have a big effect on the regression equation.
Is the p-value of a correlation significant?
You want your p-value to be as low as possible for your value to be significant. If your p-value is above your significant level (usually 1% or 5%) then your correlation is not significant. If you want to know more about the theory behind p-values, here is an easy explanation: https://www.medcalc.org/manual/correlation.php
How to interpret the p value of the Pearson coefficient?
Interpreting the Pearson Coefficient. So, to assess the statistical significance of your correlation, you need to look at the p-value that is calculated alongside the Pearson coefficient, which can be interpreted as follows: – If the p-value is low (generally less than 0.05), then your correlation is statistically significant,…
What does low p value and low are value mean?
So the $r$ value is not that impressive (usually we see $r>.5$), but the $p$-value is still significant. Usually I would think a low $r$ value would mean high $p$-value (no significant correlation), or vice versa (low $p$-value would mean a high $r$ value).
Is the R value and the p value in conflict?
The r value and the p value are not in conflict, because each one tells a different story. You could happen to get a high r value but, in case of small sample, that value could be not significant. In your case, given the large sample, it comes with no surprise that a correlation, even low-moderate, can be significant.