**5. Conclusion**

The results reported in this chapter for each experimental and theoretical application of PCA, demonstrate the versatility and capabilities of this unsupervised method to analyse samples from different origins. Three different examples were selected to show the

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relevance of PCA to elucidate specific information from a data collection in several fields. Among these issues, the following aspects must be underlined: a) the influence of the data pre-treatment on the scores and loadings values; b) the *a-priori* knowledge of the data source to select the appropriate data pre-processing; c) the strategies and criteria used for the scores and loadings plots interpretation and, d) criteria used for outliers detection, and their influence in the PCA model.

The amalgamation of the different sections included in this chapter can be used as a starting point for those researchers who are not specialists in the field, but that are interested in using these methodologies, to take the maximum advantage from their results.
