Final answer:
An increase in the p-value makes you more likely to fail to reject the null hypothesis.
Step-by-step explanation:
When conducting a hypothesis test, an increase in the p-value makes you more likely to fail to reject the null hypothesis. The p-value represents the probability of obtaining the observed data or more extreme data, assuming that the null hypothesis is true. If the p-value is greater than the predetermined significance level, typically denoted as alpha, then there is insufficient evidence to reject the null hypothesis. Therefore, an increase in the p-value makes you more likely to fail to reject the null hypothesis.