Comparing rankings
A number of organizations rank universities on factors such as research, teaching, and student satisfaction, among other factors. Three such organizations include the Times Higher Education World (THEW) University Ranking, the Academic Ranking (ARW) of World Universities, and the Center for World (CW) University Rankings. However, it's common for these organizations to give different ranks for the same university. How can you quantitatively measure the agreement or disagreement between rankings? One approach is to use a non-parametric rank correlation coefficient such as Kendall's tau.
A DataFrame with three different these three sets of rankings in rankings_df
. The packages pandas as pd
, NumPy as np
, and the stats
package from SciPy have all been loaded for you.
This exercise is part of the course
Foundations of Inference in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Compute Kendall's tau between the THEW and ARW rankings
tau_thew_arw, p_value_thew_arw = ____
# Compute Kendall's tau between the THEW and CW rankings
tau_thew_cw, p_value_thew_cw = ____
# Compute Kendall's tau between the ARW and CW rankings
tau_arw_cw, p_value_arw_cw = ____