If the probability of results occurring by chance is low, what can be inferred?

When the probability of results occurring by chance is low, it suggests that the observed findings are unlikely to have happened if the null hypothesis were true. This situation typically indicates that the data provides strong enough evidence to support the claim that there is a statistically significant effect or relationship present in the study. As a result, researchers would reject the null hypothesis, which posits that there is no effect or relationship.

Rejecting the null hypothesis does not prove that the alternative hypothesis is true but implies that the evidence suggests a departure from what was expected under the null hypothesis. This is a fundamental principle of statistical hypothesis testing, where a low p-value (often below a predetermined alpha level, such as 0.05) leads researchers to conclude that the null hypothesis can be rejected, affirming the significance of the results found in the study.

In contrast, accepting the null hypothesis would indicate no significant effect found, while conducting more research may be considered if results are inconclusive. Using a more lenient alpha level could lead to more false positives and isn't typically justified without further reasoning and contexts such as exploratory studies.