Visualizing many categories
So far in this chapter, we've only considered the case of differences in a numeric variable between two categories. Of course, many datasets contain more categories. Before you get to conducting tests on many categories, it's often helpful to perform exploratory data analysis. That is, calculating summary statistics for each group and visualizing the distributions of the numeric variable for each category using box plots.
Here, we'll return to the late shipments data, and how the price of each package (pack_price
) varies between the three shipment modes (shipment_mode
): "Air"
, "Air Charter"
, and "Ocean"
.
late_shipments
is available; dplyr
and ggplot2
are loaded.
This exercise is part of the course
Hypothesis Testing in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Using late_shipments, group by shipment mode, and calculate the mean and std dev of pack price
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