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The $$p$$-value in null hypothesis testing depends on two primary factors: the strength of the relationship in the sample (effect size) and the size of the sample. A stronger relationship and a larger sample both decrease the likelihood that a result occurred by chance under the null hypothesis, thereby yielding a lower $$p$$-value.

Factors Determining the p-value

In null hypothesis testing, sample size and relationship strength trade off against each other to determine statistical significance. A weak statistical relationship can still reach statistical significance if the sample size is sufficiently large, and conversely, a very strong relationship can be statistically significant even if it is based on a small sample.

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