The reliability of photovoltaic (PV) technology systems is a major concern to the PV industry, and the focus of much recent research activity. To ensure that these efforts return the maximum value for the resources invested, it is critical to design a study protocols that follow good statistical design principles, ensuring simplicity, avoidance of biases, minimization of missing data, reproducibility, relevance to the sceintific objective, and replication with an adequate sample size. With pre-knowledge of certain aspects of a proposed study, data science study protocols may be specified that aim to determine required sample size to adequately address the research objective. We describe the process of designing such a study protocol for an example PV technology, based upon expected uncertainties calculated from a pilot study. This represents a methodological approach to defining scientific studies that balances cost against potential information yield.