title: Interpreting statistics in the urological literature.
abstract: OBJECTIVE
  Knowledge of statistical terminology and the ability to critically interpret research findings are critical skills in the practice of evidence based medicine.
  
  
  METHODS
  We provide a series of nontechnical explanations of basic statistical concepts commonly encountered in the urological literature. In addition, we provide examples of common statistical pitfalls to increase awareness of limitations to consider when applying research findings to practice.
  
  
  RESULTS
  Statistical goals encountered in the urological literature can be broadly categorized as summarizing outcome variables, comparing 2 or more groups, measuring association among variables or predicting 1 variable from another. Errors frequently include the use of an inappropriate test for the data type of interest or using statistical testing in a manner that increases the likelihood of false-positive results. Such errors pose a threat to the validity of research findings and they may undermine study conclusions.
  
  
  CONCLUSIONS
  Editors and reviewers alike should strive for high standards of statistical analysis and reporting, and promote the publication of high quality evidence in the urological literature. The understanding of basic statistical concepts and the principles of the hypothesis testing framework is essential to the critical appraisal process and, therefore, important to all urologists. Statistical literacy should be fostered through educational materials and courses in the urological community.
authors.affiliation: Department of Surgery (Division of Urology), Duke University Medical Center, Durham, North Carolina, USA.
authors.forename: Charles D
authors.initials: CD
authors.lastname: Scales
authors.forename: Bercedis
authors.initials: B
authors.lastname: Peterson
authors.forename: Philipp
authors.initials: P
authors.lastname: Dahm
mesh_terms: D003627:Data Interpretation, Statistical; D010506:Periodicals as Topic; D014572:Urology / Q000706:statistics & numerical data*