Sampling distributions and proportions
In all the examples that we have seen, we worked with continuous variables such as beard length. However, in practice we often work with proportions such as the proportion / percentage of hipsters in the population of London. Imagine that we took a sample of 200 from the population of London and based on this sample we concluded that London's population is 10% hipster. The mean of the sampling distribution thus is 10%.
But how do we calculate the standard deviation of the sampling distribution? From the lectures, you may recall the following formula: \(\sqrt{\frac{pi * (1 - pi)}{n}}\). Let's start practicing with sampling distributions and proportions.
This exercise is part of the course
Basic Statistics
Exercise instructions
- Given that the average percentage of a sample of 200 from the London population has a percentage of hipsters of 10%, calculate the standard deviation of the sampling distributions and store this in a variable called
sample_sd.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# sample proportion
proportion_hipsters <- 0.10
# standard deviation of the sampling distribution