Texas Forensic Science Commission Licensing Practice Exam

Statistical significance is primarily determined by testing whether the p-value is less than a predetermined significance level, often denoted as alpha (α). This significance level typically represents the probability of rejecting the null hypothesis when it is actually true, commonly set at 0.05, 0.01, or 0.10.

When you conduct a hypothesis test, you calculate the p-value, which reflects the strength of the evidence against the null hypothesis. If this p-value is less than the chosen significance level, it indicates that the observed effect or difference is unlikely to have occurred by random chance alone, thereby leading to the conclusion that the results are statistically significant. This framework allows researchers to make informed decisions based on the data, ensuring that they consider the likelihood of type I errors (false positives) in their analysis.

Other options, while relevant to data analysis and interpretation, do not directly determine statistical significance. Observing the sample mean provides data but does not test significance by itself. Comparing samples across different populations can generate insights but does not conclude about significance without a p-value comparison. The margin of error offers a range around the estimate but also does not directly assess statistical significance. Therefore, the method focused on comparing the p-value to the significance level