What does a p-value of 0.05 imply about the significance of results according to the material?

What does a p-value of 0.05 imply about the significance of results according to the material?

• A. There is a 5% probability the difference is real
• B. There is a 95% probability the difference is real
• C. There were not enough animals in the experimental group to reach a conclusion
• D. The probability of finding a difference is 5%

Answer: (B)

Interpreting a p-value centers on how compatible the observed data are with the assumption that there is no real difference. A p-value of 0.05 means that, if there were truly no difference, you would expect to see results as extreme as those observed in about 5% of experiments. In many teaching materials this is described as the result being significant at the 95% level, which is why the wording about a 95% probability the difference is real is used as the best-fit interpretation in that context. Keep in mind that the p-value does not literally state the probability that the difference is real, nor does it guarantee the effect; it signals that the observed data are unlikely under no real difference and thus are deemed statistically significant at the conventional threshold. The other options don’t fit because they either misstate what the 5% represents, confuse significance with sample size or power, or treat the p-value as the probability of finding a difference without conditioning on the null hypothesis.

Interpreting a p-value centers on how compatible the observed data are with the assumption that there is no real difference. A p-value of 0.05 means that, if there were truly no difference, you would expect to see results as extreme as those observed in about 5% of experiments. In many teaching materials this is described as the result being significant at the 95% level, which is why the wording about a 95% probability the difference is real is used as the best-fit interpretation in that context. Keep in mind that the p-value does not literally state the probability that the difference is real, nor does it guarantee the effect; it signals that the observed data are unlikely under no real difference and thus are deemed statistically significant at the conventional threshold. The other options don’t fit because they either misstate what the 5% represents, confuse significance with sample size or power, or treat the p-value as the probability of finding a difference without conditioning on the null hypothesis.