Some Important Notes for Component Analysis
Component Analysis is a statistical procedure mostly used in social research where there is a large amount of data collected. This is used to bring out the unrelated data from the collection of related data, such that the principal components of the unrelated data are analyzed and their lack of relationship is established. Component Analysis means analyzing the non-related factors present in a huge sample. Within certain variables, smaller divisions are made using the principles of Component Analysis such that each component may fall in the smaller category and not related to values in another category. These differences in values are also used in research and advertisement to bring out the components of priority.
What Are Difficulties Encountered In Component Analysis Problems?
Only those models which can be predicted, say familiar products to the students, can be analyzed through Component Analysis. If the students are less familiar with the characteristics or intricacies of a component, they may be unfamiliar with the manner in which the characteristics of the product can be classified and may go wrong in categorizing them. There is the tendency of losing small amount of information if any characteristic is omitted. The more the variance, the greater is the importance of that data, so that should be the principal aim of the students when going in for Component Analysis. The most variant data will form the first component analysis, and so on. The students should have knowledge that Component Analysis is a sensitive factor to scaling of variables present in a data, which should be clarified by the students before presenting information through Component Analysis.
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