Generated by Gemini:I'couldn't find the answer in your document, but here is what I found on the web:
A p-value is a statistical measurement used to assess the validity of a hypothesis. It represents the probability of obtaining results at least as extreme as the observed ones, assuming the null hypothesis (the default position that there's no effect) is true.
In simpler terms, a low p-value (generally accepted as 0.05 or less) indicates strong evidence against the null hypothesis, suggesting that the observed effect is likely not due to random chance. Conversely, a high p-value suggests that the observed effect could be due to random chance, and more evidence is needed to reject the null hypothesis.
It's important to note that p-values alone shouldn't be the sole factor in determining the significance of a result. Other factors like effect size and research design should also be considered.
