Medical Statistics II: Probability and Inference
After learning how to define the features of a data set in Medical Statistics I, what’s next? Through the use of statistical inference, you can draw conclusions about a population based on a representative sample.
What is contributing to higher rates of COVID-19 in millennials than Gen Z? Why are some ethnic groups predisposed to childhood obesity? What factors are contributing to a higher prevalence of cancer in some regions of the country? By expressing the probability of an event occurring rather than declaring it as a fact, you can address uncertainties and generalize your findings.
- Use statistical inference to make predictions about data using hands-on computer simulations in R or SAS
- Understand the foundations of probability, including basic probability, probability distributions, standard error, confidence intervals, p-values, statistical power, Type I and Type II error, Bayesian statistics, and equivalence testing
- Recognize common statistical misconceptions and errors using real-life examples from medical journals and the popular press
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.
View the full accreditation information HERE from Stanford Medicine
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