Which of the following confidence levels indicates a higher stringency for statistical significance in bone density studies?

• A. 85% confidence level
• B. 90% confidence level
• C. 95% confidence level
• D. 80% confidence level

Answer: (C)

In bone density studies, the confidence level reflects the degree of certainty researchers have in their results, specifically regarding the interval estimate of the population parameter. A 95% confidence level indicates that researchers can be 95% confident that the true population parameter lies within the calculated confidence interval. This level suggests that out of 100 intervals constructed from separate random samples, approximately 95 of them would contain the true population mean.

Higher confidence levels, such as 95%, imply a stricter criterion for statistical significance. This means that researchers need stronger evidence to reject the null hypothesis, as a higher confidence level reduces the likelihood of Type I errors (false positives), where researchers incorrectly conclude that there is a significant effect or difference when there is none.

In contrast, lower confidence levels like 80% or 85% would suggest a greater tolerance for uncertainty, allowing for a higher probability of committing Type I errors. Consequently, the 95% confidence level is typically utilized in clinical and research settings to ensure robust and reliable findings in bone density studies and other biomedical research areas, emphasizing rigorous statistical significance.