In other words, there is a likelihood of 1/10,000,000,000,000,000,000,000,000,000,000,000,000 that the statistical result was due to random chance.
In more casual sciences p < 0.05 is considered the limit of significance, i.e. less than 1/20 likelihood of statistical testing favoring the tested hypothesis over the null hypothesis due to random chance
If you are testing a single hypothesis, sure. But nowadays, statistics training really weighs on bonferroni correction, or other methods to deal with the issue raised by the above-referenced XKCD, whentesting multiple hypotheses.
In more casual sciences p < 0.05 is considered the limit of significance, i.e. less than 1/20 likelihood of statistical testing favoring the tested hypothesis over the null hypothesis due to random chance