How Many Injections Are Really Enough?

This presentation draws from two articles by Bob Pirok from the University of Amsterdam:

How Many Repetitions Do I Need? Caught Between Sound Statistics and Chromatographic Practice

How to Meaningfully Describe and Display Analytical Data? A Dive Into Descriptive Statistics

Together, these works explore one of the most persistent challenges in analytical chemistry: how to balance statistical soundness with the practical constraints of time, budget, and sample availability. In chromatography, as in much of analytical science, the goal is not only to generate data, but to generate trustworthy data—data that can withstand scrutiny, guide decisions, and meet regulatory expectations.

The first article examines the critical question of replication. It highlights that while additional injections or measurements strengthen statistical confidence, the relationship between replication and certainty is not linear. The largest gains in precision occur in the early stages, for example, increasing from two to five replicates can dramatically narrow confidence intervals, significantly improving data reliability without excessively consuming resources. These insights help analysts make informed decisions about how many injections are truly “enough” to balance quality with efficiency.

The second article builds on this foundation by focusing on data interpretation. It examines how our choice of statistical tools—whether mean vs. median or standard deviation vs. median absolute deviation (MAD)—shapes our understanding of chromatographic data. Robust statistics, less sensitive to outliers, offer a truer picture of experimental variation, helping analysts avoid misleading conclusions from a single rogue data point.

By combining these two perspectives, this presentation emphasizes that meaningful chromatography requires more than good separation; it demands thoughtful experimental design, statistically aware data treatment, and honest visualization. Whether deciding how many replicates to run or how best to summarize results, adopting these evidence-based practices strengthens analytical confidence, reduces risk, and ensures that chromatographic conclusions truly reflect the underlying science.