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LQCL2503 - CMLE - The Impact of Outliers on the Results of Correlation Analysis in Clinical Laboratory Data
Course Description

LabQ 2025 Clinical Laboratory: Clinical Chemistry  

Faculty/Authors

Michal Ordak, PhD
Department of Pharmacotherapy and Pharmaceutical Care
Faculty of Pharmacy
Medical University of Warsaw
Warsaw, Poland 

CMLE Credit: 2.0
Estimated Completion Time: 2 hour
Format: Online Educational Activity and Post Exam

Instructions

To claim CMLE credit for the exercise, do the following:

  1. Review the Technical Considerations.
  2. Click Go to Course to view an overview of the modules in this course.
  3. Click Access to begin the course.
  4. Review the Educational Activity.
  5. Complete and submit the Post Exam.
  6. Submit the course Evaluation to register your credit.

Faculty Disclosures​
The faculty have no relevant financial relationships with commercial interests to disclose.

Technical Considerations

Release Date: 5/31/2025 
Review Date:
Expiration Date: 12/31/2027 

Course Objectives
Following completion of this activity, you will be able to:

  • explain how outliers can influence the results of correlation analysis in clinical laboratory data; 

  • describe the potential diagnostic misinterpretations caused by improper correlation analysis; 

  • identify the differences between Pearson’s and Spearman’s correlation methods in the presence of outliers; and 

  • recognize the importance of identifying outliers before performing correlation analysis. 

Summary
Availability:
On-Demand
Credit Offered:
2 CMLE Credits
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