Canadian Health Information Management Association Exam 2025 – 400 Free Practice Questions to Pass the Exam

When a difference is statistically significant at a level of 0.05, it indicates that there is only a 5% probability that the observed difference is due to random variation or chance. In other words, it is unlikely that the difference would occur if there was actually no real effect. This level of significance is commonly used in research to establish whether a result is meaningful or could potentially be attributed to random fluctuations in the data.

The implication is that the evidence is strong enough to reject the null hypothesis, suggesting that the difference observed is real and not likely due to chance factors. This conclusion is crucial in research, helping to ensure that findings are robust and can be acted upon with confidence.

Understanding the context of this statistical significance helps underscore the importance of rigor in scientific inquiry, as well as the critical role that p-values play in interpreting data. A significance level of 0.05 consistently supports the interpretation that significant differences contribute to our understanding of the population from which data was drawn.