Finding outliers using IQR
Interquartile range, or IQR, is another way of measuring spread that's less influenced by outliers. IQR is also often used to find outliers. If a value is less than \(\text{Q1} - 1.5 \times \text{IQR}\) or greater than \(\text{Q3} + 1.5 \times \text{IQR}\), it's considered an outlier. In fact, this is how the lengths of the whiskers in a ggplot2 box plot are calculated.
In this exercise, you'll calculate IQR and use it to find some outliers. Both dplyr and ggplot2 libraries are loaded and food_consumption is available.
This exercise is part of the course
Introduction to Statistics in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Compute the 25th percentile and 75th percentile of co2_emission
q1 <- quantile(___$___, ___)
q3 <- ___
# Compute the IQR of co2_emission
iqr <- ___
iqr