This text gives graduate students with diverse backgrounds across the health, medical, social, and mathematical sciences a solid, unified foundation in the principles of statistical inference. Drawing on his extensive experience teaching graduate-level biostatistics courses and working in the pharmaceutical industry, the author covers the theoretical underpinnings essential to understanding subsequent core methodologies in the field. Extended examples illustrate key concepts in depth using a specific biostatistical context and simple R functions are provided for conducting simulation studies.