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Statistics for Medical Professionals (CME)

Tuesday, September 23, 2014 to Monday, August 19, 2019
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This course seeks to fulfill the need in the clinical community to better understand medical statistics as it pertains to practicing evidence based medicine, communicating treatment outcome probability to patients and interpreting the results of studies and scientific papers, and in turn improving quality of patient care. This applies to all specialties in various settings of practice.


This course is designed to meet the educational needs of an international audience of physicians, residents and medical researchers in all specialties.


  • Release Date: September 23, 2014
  • Latest Review Date: August 19, 2016
  • Expiration Date: August 19, 2019
  • Estimated Time to Complete: 23.50 hours
  • CME Credits Offered: 23.50
  • Registration Fee: $25.00

To Obtain CME Credits

  • Review the information below and complete the entire activity
    • Complete the CME post-test, CME assessment survey, and attestation question at the end of the course
    • You must receive a score of 75% or higher on the 30 question post-test in order to receive a CME certificate. You will have two attempts per question (or one attempt for questions with only two options) to pass the post-test.
    • Once you attest to completing the entire online activity and have scored 75% or higher, your CME Certificate will be generated automatically and will be available on your Dashboard page.
  • *Participation in discussion forums, practice quizzes, content marked OPTIONAL, and additional readings are not certified for AMA PRA Category 1 Credit™.

Learning Objectives

  • At the conclusion of this activity, participants should be able to:
    • Develop strategies to enable translation of medical research into practicing evidence-based medicine through the following statistical methods: understanding bias, random variation, correctly interpret P values, basic probability and conditional probability, spot statistical errors, understand correlated data.
    • Develop strategies to use specific statistical tests, understand basic regression modeling, and Bayesian inference.
    • Develop strategies to effectively communicate prognosis and treatment probabilities to patients.
    • Develop strategies to enable consistent interpretation of research data and provide correct information on study results.
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