The use of nonparametric statistics in quantitative electron microscopy

Parametric statistical methods assume samples that have a normal distributi on and representative sample sizes (i.e. n >20). Quantitative electron micr oscopy is inherently restricted to small sample sizes and a priori there is no way to know if the expression of the ligand being studied has a normal distribution. Thus to make statistical inferences based on data generated b y quantitative electron microscopy using parametric methods may not be just ified. Non-parametric statistical methods offer a tool for the evaluation o f data that do not meet the criteria for analysis by parametric methods. In this report I show the utility of using nonparametric statistical methods for the analysis of data generated by quantitative electron microscopy.