Statistics for Doctors: Confidence Intervals

Abstract Confidence intervals (CIs) are an important statistical tool that helps estimate the range in which a true population value is likely to fall. This paper explains what CIs are, how they work, and their role in medical and life sciences research. Using examples like blood pressure measurements, treatment success rates, and survival times, we show how CIs provide a clearer picture than single-value estimates. We also explore how sample size and standard error affect the width of CIs, with larger samples leading to more precise estimates. Additionally, we discuss the use of CIs in studies such as drug comparisons, diagnostic tests, and regression models. This paper highlights how confidence intervals improve medical decision-making by helping researchers and doctors understand data more accurately and avoid misleading conclusions.