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The best quest is subjective, as stated by Josh Stommer in the Stat Quest tutorial on principle component analysis. In this tutorial, he explains the main ideas behind PCA in five minutes, providing an overview of the concepts. Using the example of normal cells, which could represent different entities such as people, cars, or cities, Stommer illustrates how PCA can help identify underlying differences by sequencing messenger RNA to understand gene activity. This method allows for distinguishing characteristics that are not visible externally, providing insights into the behavior or characteristics of the entities being analyzed. It is a useful tool for identifying patterns and relationships within large datasets.