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  3. Experimental Design in R

Exercise

NHANES EDA

Let's examine our newly constructed dataset with a mind toward EDA. As in the last chapter, it's a good idea to look at both numerical summary measures and visualizations. These help with understanding data and are a good way to find data cleaning steps you may have missed. The nhanes_combined dataset has been pre-loaded for you.

Say we have access to NHANES patients and want to conduct a study on the effect of being told by a physician to reduce calories/fat in their diet on weight. This is our treatment; we're pretending that instead of this being a question asked of the patient, we randomly had physicians counsel some patients on their nutrition. However, we suspect that there may be a difference in weight based on the gender of the patient - a blocking factor!

Instructions

100 XP
  • Fill in and run the dplyr code to find mean weight (bmxwt) in kg by our treatment (mcq365d). Is there anything interesting about the NA treated patients?
  • Fill in the ggplot2 code to look at a boxplot of the IQR of patients' weights by the treatment variable.