Test correlation for significance: If there is a correlation in the sample, it still has to be checked whether this correlation also exists in the population. The question therefore arises as to the amount above which a correlation coefficient can be considered statistically significant.

The significance of correlation coefficients can be checked with the help of a t-test. As a rule, it is tested whether the correlation coefficient is significantly different from zero, i.e. linear independence is tested. In this case, the null hypothesis is that there is no correlation in the population. In contrast, the alternative hypothesis assumes that there is a correlation.

As with any other hypothesis test, the significance level is first set, usually at 5 %. If the calculated p-value is below 5%, the null hypothesis is rejected and the alternative hypothesis applies.

Here you can find more information on correlation analysis:
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Here you can calculate a correlation online:
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