Hypothesis testing I: Proportions

Kelly H. Zou, Julia R. Fielding, Stuart G. Silverman, Clare M.C. Tempany

Research output: Contribution to journalReview articlepeer-review

47 Scopus citations


Statistical inference involves two analysis methods: estimation and hypothesis testing, the latter of which is the subject of this article. Specifically, Z tests of proportion are highlighted and illustrated with imaging data from two previously published clinical studies. First, to evaluate the relationship between nonenhanced computed tomographic (CT) findings and clinical outcome, the authors demonstrate the use of the one-sample Z test in a retrospective study performed with patients who had ureteral calculi. Second, the authors use the two-sample Z test to differentiate between primary and metastatic ovarian neoplasms in the diagnosis and staging of ovarian cancer. These data are based on a subset of cases from a multiinstitutional ovarian cancer trial conducted by the Radiologic Diagnostic Oncology Group, in which the roles of CT, magnetic resonance imaging, and ultrasonography (US) were evaluated. The statistical formulas used for these analyses are explained and demonstrated. These methods may enable systematic analysis of proportions and may be applied to many other radiologic investigations.

Original languageEnglish (US)
Pages (from-to)609-613
Number of pages5
Issue number3
StatePublished - Mar 1 2003


  • Statistical analysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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