Principal component analysis (PCA) can be used with variables of…

Question Answered step-by-step Principal component analysis (PCA) can be used with variables of… Principal component analysis (PCA) can be used with variables of any mathematical types: quantitative, qualitative, or a mixture of these types. (True/False question). PCA biplots are graphs in which objects and variables (descriptors) are represented together. (True/False question). 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). (Multiple choice question) Which of the following are true about PCA? PCA is an unsupervised method It searches for the directions that data have the largest varianceMaximum number of principal components is less or equal than number of initial variablesAll principal components are orthogonal to each other A. 1 and 2B. 1 and 3C. 2 and 3D. 1, 2 and 3E. 1,2, 3 and 4                              Math Statistics and Probability STAT 220:231 Share QuestionEmailCopy link Comments (0)