1. Principal component analysis (PCA) can be used with variables of any mathematical types: quantitative, qualitative, or a mixture of these types. (True/False question).

1. PCA biplots are graphs in which objects and variables (descriptors) are represented together. (True/False question).

1. Complete linkage in the hierarchical clustering compute all pairwise dissimilarities between the observations in cluster A and the observations in cluster B, and record the smallest of these dissimilarities. (True/False question).

1. (Multiple choice question) Which of the following are true about PCA?
2. PCA is an unsupervised method
3. It searches for the directions that data have the largest variance
4. Maximum number of principal components is less or equal than number of initial variables
5. All principal components are orthogonal to each other

A. 1 and 2

B. 1 and 3

C. 2 and 3

D. 1, 2 and 3

E. 1,2, 3 and 4