Description
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
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