Statistical concepts form the foundation for designing, analyzing, and interpreting epidemiological studies. This chapter introduces the normal curve as a fundamental probability distribution in statistical inference and explains its role in representing population variability. It then clarifies the distinction between standard deviation, which measures variability in data, and standard error, which reflects the precision of an estimate. Finally, it addresses Type I error (false positives), Type II error (false negatives), and statistical power, highlighting their implications for hypothesis testing and study validity. A clear understanding of these concepts is essential for critically evaluating research findings and ensuring sound methodological practice in epidemiology.