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!

แบบฝึกหัดนี้เป็นส่วนหนึ่งของหลักสูตร

Experimental Design in R

ดูคอร์ส

คำแนะนำการฝึกหัด

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.

แบบฝึกหัดเชิงโต้ตอบแบบลงมือทำ

ลองทำแบบฝึกหัดนี้โดยเติมโค้ดตัวอย่างนี้ให้สมบูรณ์

# Fill in the dplyr code
___ %>% 
  group_by(___) %>% 
  summarize(mean = mean(___, na.rm = TRUE))

# Fill in the ggplot2 code
___ %>% 
  ggplot(aes(as.factor(___), ___)) +
  geom_boxplot() +
  labs(x = "Treatment",
       y = "Weight")

แก้ไขและรันโค้ด