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In page Philosophy of science:

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The problem of induction discussed above is seen in another form in debates over the foundations of statistics.[1] The standard approach to statistical hypothesis testing avoids claims about whether evidence supports a hypothesis or makes it more probable. Instead, the typical test yields a p-value, which is the probability of the evidence being such as it is, under the assumption that the null hypothesis is true. If the p-value is too high, the hypothesis is rejected, in a way analogous to falsification. In contrast, Bayesian inference seeks to assign probabilities to hypotheses. Related topics in philosophy of statistics include probability interpretations, overfitting, and the difference between correlation and causation.[citation needed]