Consumer ratings play a pivotal role in making purchase decision and are now part of daily decision making. Yet, there always be a concern on the credibility of these ratings. Numerous incidents have occurred in the past where businesses gave incentives to the raters to provide fraud and non-credible reviews. We, as average users, tend to believe recommendations given by people with whom we have close relationship, such as family or friends. In the absence of people that we can inherently trust, we tend to consider ratings that come from popular raters more seriously. This is particularly true in the online environments where many raters are unknown to us. However, we can never be sure how trustworthy these popular raters are when providing their ratings and reviews. This paper investigates the credibility of the most popular users in giving trustworthy ratings on a popular consumer reviews platform Yelp. We begin by identifying and grouping the most popular users. We then collect all ratings of the businesses that this group of users has rated. Endogenous statistical techniques are employed to determine the trustworthiness of each popular user's rating and to discount the unfair ratings. By analyzing and comparing the rating given by each popular user with the computed business’ trust rating, we collect statistics that found the most popular users are not always trustworthy in providing their ratings and their percentage of rating trustworthiness.