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Medical Statistics I: Introduction to Data Analysis and Descriptive Statistics


Medical Statistics I: Introduction to Data Analysis and Descriptive Statistics Banner

  • Overview
  • Faculty
  • Begin


Date & Location
Monday, May 15, 2023, 12:00 AM - Thursday, May 14, 2026, 11:59 PM, On Demand

Overview
Medical Statistics I is the first in a three-course statistics series. Medical Statistics I covers the foundations of data analysis, programming in either R or SAS (students may use either program), descriptive statistics, visualizing data, study design, and measures of disease frequency and association. The course uses real examples from the medical literature and popular press. Participants will learn how to critically evaluate the statistics in medical studies. The course also prepares participants to be able to analyze their own data.

Prerequisites: There are no prerequisites for this course. Students will need to be familiar with a few basic math tools: summation sign, factorial, natural log, exponential, and the equation of a line; a brief tutorial is available on the course website for students who need a refresher on these topics.

What you will learn

- Basic programming in either SAS or R. 
- How to visualize and describe data.
- How to calculate and interpret measures of disease frequency and association. 

Registration

  Original Release Date: February 1, 2020
  Review Date: May 17, 2023
  Expiration Date: May 14, 2026
  Estimated Time to Complete: 13 Hours
  Registration Fee: See fee schedule on registration.

Click Begin (at the top) to learn more about how to enroll in the course. 


Credits
AMA PRA Category 1 Credits™ (13.00 hours), Non-Physician Participation Credit (13.00 hours)

Target Audience
Specialties - Non-clinical
Professions - Fellow/Resident, Non-Physician, Physician, Student

Objectives
At the conclusion of this activity, participants should be able to:

  1. Analyze, interpret, describe, and visualize data
  2. Complete basic programming in R or SAS
  3. Analyze the foundations of probability and statistical inference
  4. Review statistical tests and graphs used in medical research
  5. Consider common statistical pitfalls and errors.

Accreditation

In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.

Credit Designation

American Medical Association (AMA)
Stanford Medicine designates this Enduring Material for a maximum of 13.00 AMA PRA Category 1 CreditsTM. Physicians should claim only the credit commensurate with the extent of their participation in the activity.


Additional Information

Cultural and Linguistic Competency
The planners and speakers of this CME activity have been encouraged to address cultural issues relevant to their topic area for the purpose of complying with California Assembly Bill 1195. Moreover, the Stanford University School of Medicine Multicultural Health Portal contains many useful cultural and linguistic competency tools including culture guides, language access information and pertinent state and federal laws.  You are encouraged to visit the Multicultural Health Portal: http://lane.stanford.edu/portals/cultural.html

Reference/Bibliography List
For additional resources, please visit the course.

For activity related questions, please contact
  650.204.3984
  [email protected]



Mitigation of Relevant Financial Relationships


Stanford Medicine adheres to the Standards for Integrity and Independence in Accredited Continuing Education.

The content of this activity is not related to products or the business lines of an ACCME-defined ineligible company. Hence, there are no relevant financial relationships with an ACCME-defined ineligible company for anyone who was in control of the content of this activity. 

Member Information
Role in activity
Nature of Relationship(s) / Name of Ineligible Company(s)
Lesley S Park, PhD, MPH
Research Scientist
Stanford
Co-Course Director
Kristin Sainani, PhD
Associate Professor
Stanford University
Co-Course Director
Jackie Peterson
Program Manager
Stanford
Reviewer

Medical Statistics I: Introduction to Data Analysis and Descriptive Statistics

INSTRUCTIONS: Click "Launch Website" to enroll on our external learning management system (LMS). With successful completion at the end of the course, an evaluation and claim credit url link will be provided to you to access the Stanford CME MY CE Portal with more detailed instructions.

Launch Website

 

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