Integrating Experimental Design and Statistics Throughout an Undergraduate Human Physiology Laboratory Course
Gregory J. Mitchell, Erica A. WehrweinStatistical analysis is central to the study of physiology, yet many undergraduate students struggle to apply statistical reasoning to physiological studies. Although statistics or biostatistics coursework is commonly required in a degree program, students often perceive statistics as disconnected from physiological experimentation, leading to difficulty selecting and justifying, statistical reasoning in a physiological context. Here, we describe a course-level instructional model in an upper-division physiology laboratory that holistically integrates descriptive statistics and inferential biostatistics across a semester-long undergraduate laboratory course. Rather than treating statistics as a standalone topic, statistical reasoning is embedded throughout weekly laboratory activities, lecture discussions, in-class worksheets, post-laboratory assignments, and a capstone project. Each laboratory emphasizes a specific statistical test aligned with the experimental design while reinforcing foundational concepts such as hypotheses, variables, experimental conditions, sample size, data visualization, and interpretation. This article outlines the structure of this integrated approach, illustrates how statistical concepts are revisited across physiological systems, and provides a practical, adaptable framework for physiology educators seeking to strengthen statistical reasoning within laboratory curricula.