When conducting statistical hypothesis tests, researchers often use the p-value to determine the significance of their findings. The p-value represents the probability of observing a result as extreme as, or more extreme than, the one obtained if the null hypothesis (a statement of no effect) were true. Researchers strive to obtain p-values that are small enough to reject the null hypothesis and support their alternative hypothesis.<\/p>\n
One common misconception is that a larger sample size alone can reduce the p-value. However, this claim needs closer examination.<\/p>\n