title: The use of nonparametric statistics in quantitative electron microscopy.
abstract: Parametric statistical methods assume samples that have a normal distribution and representative sample sizes (i.e. n >20). Quantitative electron microscopy 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 by quantitative electron microscopy using parametric methods may not be justified. Nonparametric statistical methods offer a tool for the evaluation of 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.
authors: Department of Cell Biology, Neurobiology and Anatomy, University of Cincinnati, College of Medicine, OH 45267-0521, USA. Randal.Morris@UC.Edu
authors: R E
authors: RE
authors: Morris
mesh_terms: D000818:Animals; D001427:Bacterial Toxins / Q000378:metabolism; D002460:Cell Line; D002478:Cells, Cultured; D005347:Fibroblasts / Q000737:chemistry / Q000648:ultrastructure; D008168:Lung / Q000737:chemistry / Q000166:cytology / Q000648:ultrastructure; D051379:Mice; D016253:Microscopy, Immunoelectron / Q000379:methods* / Q000706:statistics & numerical data*; D016011:Normal Distribution; D011510:Proteolipids / Q000378:metabolism / Q000648:ultrastructure; D037661:Pulmonary Surfactant-Associated Proteins; D011663:Pulmonary Surfactants / Q000378:metabolism / Q000648:ultrastructure; D051381:Rats; D017207:Rats, Sprague-Dawley; D011956:Receptors, Cell Surface / Q000378:metabolism / Q000648:ultrastructure; D020545:Respiratory Mucosa / Q000737:chemistry / Q000166:cytology / Q000648:ultrastructure; D018709:Statistics, Nonparametric
chemical_list: D001427:Bacterial Toxins; D011510:Proteolipids; D037661:Pulmonary Surfactant-Associated Proteins; D011663:Pulmonary Surfactants; D011956:Receptors, Cell Surface