In the surveys of the credibility of makeup products according to users statistics will be used in this IA to evaluate and measure the patterns that are present in makeup reviews Descriptive statistics will be used to summarize and present the significant characteristic features of the different features Hypothesis testing will be used within the investigation to understand whether certain observed trends and patterns are significant so that it is possible to determine if some makeup products were positively or negatively reviewed throughout all of them It is possible to use regression analysis to identify correlations between certain product attributes and user satisfaction thus developing a more precise perspective on credibility factors I will be providing a framework that will allow the reader to understand the trustworthiness of beauty products when new reviews become available This adaptive approach enables the fine tuning nature of evaluations with changing datasets Finally statistical methods will not only help quantify the validity of makeup products but also increase the reliability and rigor embedded in our conclusions hence making this potential discipline more evidence driven