We have 16 variables which are indices produced by calculations based on ratio (unitless in fact). Some examples of the ranges of our variables are (0.450-0.750), (0.000 - 0.800) and (0.000 - 1.000). Based on this data, we want to apply hierarchical and K-means clustering algorithms. According to the literature, it is recommended to apply standardization before PCA and clustering follows this. In our case, covariance matrix is proposed for PCA but we are not sure we should apply standardization before this process.
If you could help us in this issue, we would be glad.
Thanks in advance for your answers.