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This week you have been learning about from your readings about the critical components of data analysis, including bias, causality, confounding, and interaction. It also covers more in-depth discussion of study designs, as well as a comprehensive review of ways to report on randomized and nonrandomized studies. So what do these mean to you as an advanced practice nurse? How are you able to see the connection between the numbers on the page and ways you might apply this in a practice situation? How is this data important to your role as an advanced practice nurse. Why is it important to know how to calculate and interpret prevalence and incidence rates of diseases? Why are mortality and morbidity rates important? Why is the sensitivity of a specific test important? What about relative risks.
Most nurses don’t like what we call numbers or statistics it is as if our brains just want to shut off but understanding how to interpret these results and numbers is important to population health interventions in what way?
