The analysis of clinical samples, population samples, and controlled trials is typically subjected to rigorous statistical review. This fact is understandable, given that the results of clinical investigation will often be used to inform patient care or clinical decision making. One would not want to predicate patient advice on research findings that are not correctly interpreted or valid. For this reason, most major journals publishing clinical research include statistical reviews as a standard component of manuscript evaluation for publication. Clinical data, regardless of publication venue, are often subject to rather uniform principles of review. In contrast, basic science studies are often handled less uniformly, perhaps because of the unique challenges inherent in this type of investigation. A single basic science manuscript, for example, can span several scientific disciplines and involve biochemistry, cell culture, model animal systems, and even selected clinical samples. Such a manuscript structure is a challenge for analysis and statistical review. Not all journals publishing basic science articles use statistical consultation, although it is becoming increasingly common. 1 In addition, most statistical reviewers are more comfortable with clinical study design than with basic science research. Consequently, there are multiple reasons why the statistical analysis of basic science research might be suboptimal. In this review, we focused on common sources of confusion and errors in the analysis and interpretation of basic science studies. The issues addressed are seen repeatedly in the authors’ editorial experience, and we hope this article will serve as a guide for those who may submit their basic science studies to journals that publish both clinical and basic science research. We have discussed issues related to sample size and power, study design, data analysis, and presentation of results (more details are provided by Katz2 and Rosner3). We then illustrated these issues using a set of examples from basic science research studies.