3/9/2024 0 Comments Xlstat add in![]() ![]() ![]() ![]() If the information associated with the first 2 or 3 axes represents a sufficient percentage of the total variability of the scatter plot, the observations could be represented on a 2 or 3-dimensional chart, thus making interpretation much easier. PCA dimensions are also called axes or Factors. It is a projection method as it projects observations from a p-dimensional space with p variables to a k-dimensional space (where k < p) so as to conserve the maximum amount of information (information is measured here through the total variance of the dataset) from the initial dimensions. It is widely used in biostatistics, marketing, sociology, and many other fields. Principal Component Analysis is one of the most frequently used multivariate data analysis methods that lets you investigate multidimensional datasets with quantitative variables. What is principal component analysis? Definition of a Principal Component Analysis ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |