National Board Dental Hygiene Examination (NBDHE) Dental Hygienist Practice Test

In statistical terms, what does a low p-value indicate about a null hypothesis?

1. It should be accepted

2. It is likely to be rejected

3. It is proven to be true

4. It is irrelevant

The correct answer is: It is likely to be rejected

A low p-value in statistical analysis indicates that the observed data is unlikely to have occurred under the assumption that the null hypothesis is true. Essentially, this suggests that the evidence against the null hypothesis is strong enough that researchers may choose to reject it. In hypothesis testing, the null hypothesis typically states that there is no effect or no difference in the studied parameters. A low p-value, typically below a predefined threshold (commonly 0.05), implies that the results observed in the data would be very rare if the null hypothesis were correct. Therefore, it provides substantial evidence to consider the alternative hypothesis as a more plausible explanation for the data. This decision to reject the null hypothesis does not prove the alternative hypothesis to be true, but it does suggest that there is a statistically significant effect or difference that merits further investigation. In this context, the other options do not accurately represent the role of the p-value in hypothesis testing. Accepting the null hypothesis would imply that there is not enough evidence against it, which is not the case when a low p-value is present. Stating that the null hypothesis is proven true misrepresents the nature of hypothesis testing, where we generally do not prove hypotheses but rather assess evidence for or against them. Finally,