What is the significance of a p-value being set at greater than or equal to 0.05?

A p-value greater than or equal to 0.05 indicates that the results are not statistically significant at the conventional threshold used in hypothesis testing. This means that there is not enough evidence to reject the null hypothesis, which typically states that there is no effect or difference. Researchers often use this threshold to determine whether to conclude that any observed effect in their data is likely due to random chance rather than a true effect in the population.

When the p-value is below 0.05, it suggests a strong enough statistical result to suggest that the null hypothesis may not hold, therefore implying statistical significance. A p-value of 0.05 or higher does not imply an absence of effect; rather, it indicates that if a true effect exists, the evidence in this particular study is insufficient to demonstrate its relevance statistically.

Thus, setting a p-value at greater than or equal to 0.05 serves as a guideline for determining when statistically significant evidence is present; values above this threshold do not provide the necessary support for such conclusions.