**Core Concept**
The p-value is a statistical measure that indicates the probability of observing results at least as extreme as those observed during the experiment, assuming that the null hypothesis is true. It is used to determine the significance of the findings, with a smaller p-value indicating stronger evidence against the null hypothesis.

**Why the Correct Answer is Right**
A p-value of 0.01 means that if the null hypothesis were true, there would be only a 1% chance of observing the results obtained in the study. This is a relatively low probability, indicating that the results are statistically significant and unlikely to occur by chance. The investigator can reject the null hypothesis and conclude that the observed effect is real.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because a p-value of 0.01 does not indicate the probability of the null hypothesis being true or false. Instead, it provides a measure of the probability of observing the results, assuming the null hypothesis is true.
**Option B:** This option is incorrect because a p-value of 0.01 does not indicate the strength or magnitude of the effect observed in the study. It only provides a measure of the statistical significance of the findings.
**Option C:** This option is incorrect because a p-value of 0.01 does not indicate the probability of the alternative hypothesis being true. Instead, it provides a measure of the probability of observing the results, assuming the null hypothesis is true.

**Clinical Pearl / High-Yield Fact**
When interpreting p-values, it's essential to consider the study's sample size, the type of statistical test used, and the research question being addressed. A p-value of 0.01 may not be as impressive if the study had a large sample size or used a conservative statistical test.

**Correct Answer: C. It means that there is only a 1% chance of observing the results, assuming the null hypothesis is true.**