News reports and communication are inherently constrained by space, time, and attention. As a result, news sources often condition the decision of whether to share a piece of information on the similarity between the signal and the prior belief of the audience, which generates a sample selection problem. This paper experimentally studies how people form beliefs in these contexts, in particular the mechanisms behind errors in statistical reasoning. I document that a substantial fraction of experimental participants follows a simple "what you see is all there is" heuristic, according to which they exclusively take into account information that is right in front of them, and directly use the sample mean to estimate the population mean. A series of treatments aimed at identifying mechanisms suggests that for many participants unobserved signals do not even come to mind. I provide causal evidence that the frequency of such incorrect mental models is a function of the computational complexity of the decision problem. These results point to the context-dependence of what comes to mind and the resulting errors in belief updating.