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Demystifying Data: A Modern Approach to Statistical Understanding


Demystifying Data: A Modern Approach to Statistical Understanding Banner

  • Overview
  • Faculty
  • Begin


Date & Location
Thursday, October 3, 2024, 12:00 AM - Saturday, October 2, 2027, 11:59 PM, On Demand

Overview
This foundational statistics course provides a practical toolkit for professionals who apply, interpret, or engage with statistics and data-based evidence in their job or daily life. Through the two co-instructors’ video podcast-style approach based on case studies and stories, students will learn to “peer under the hood” of statistical claims, reports and dashboards to ask critical questions, such as: What is the data backstory? How were the data collected, processed and adjusted? What do the reported numbers mean—and what don’t they mean? What are alternate ways to present and understand the numbers? and How trustworthy are the results? The course incorporates example datasets from varied domains, including medicine, healthcare, business, government, education, social science, and psychology. The course emphasizes concepts and intuition over formulas and does not require any statistical programming, though an optional introduction to statistical programming with R is included at the end. This course will prepare students for taking more advanced courses in statistics, data science, and epidemiology, including the Medical Statistics Program and the Clinical Trials course.

Registration

  Release Date: October 3, 2024
  Expiration Date: October 2, 2027
  Estimated Time to Complete: 11.0 hours
  Registration Fee: $675

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


Credits
AMA PRA Category 1 Credits™ (11.00 hours), Non-Physician Participation Credit (11.00 hours)

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

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

  1. Discuss how raw data is transformed into evidence-based conclusions, including through data smithing and statistical adjustment
  2. Recognize problems and pitfalls in data collection and statistical analyses, including common biases and fallacies
  3. Distill, summarize, and visualize data to answer specific questions and support claims
  4. Utilize statistical tools for evaluating the trustworthiness of conclusions, including confidence intervals and p-values.

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 11.00 AMA PRA Category 1 CreditsTM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity. 


Additional Information

Accessibility Statement
 Stanford University School of Medicine is committed to ensuring that its programs, services, goods and facilities are accessible to individuals with disabilities as specified under Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Amendments Act of 2008.  If you have needs that require special accommodations, including dietary concerns, please contact the CME.

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: https://laneguides.stanford.edu/multicultural-health

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

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

For CME general questions, please contact 
   Email: [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)
Regina Nuzzo, PhD
Co-Course Director
Nothing to disclose
Kristin Sainani, PhD
Associate Professor
Stanford University
Co-Course Director
Jacklyn Peterson, BA
Program Manager
Stanford University
Planner
Charles Grant Prober, MD
Senior Associate Vice Provost for Health Education
Stanford University
Reviewer

Demystifying Data Module
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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