What does it mean if a result has a p-value of 0.03?

A p-value of 0.03 indicates that there is a significant difference between the groups being compared in a statistical analysis. In hypothesis testing, the p-value helps determine whether to reject the null hypothesis, which typically states that there is no effect or difference. A p-value of 0.03 suggests that the probability of observing the data, or something more extreme, given that the null hypothesis is true, is only 3%. This low probability typically leads researchers to consider the result statistically significant if they are using a common significance level of 0.05.

In this context, a p-value less than the threshold indicates that the evidence against the null hypothesis is strong enough to suggest a meaningful difference exists in the population from which the samples were drawn. This finding prompts further investigation and generally supports the idea that the effect being measured is likely real rather than a product of random chance.

The other options do not accurately reflect what a p-value of 0.03 means in statistical analysis. Conclusively, the interpretation of the p-value provides an essential foundation for decision-making in the context of research findings.