Business decisions are increasingly based on data and statistical analyses. Managerial intuition plays an important role at various stages of the analytics process. It is thus important to understand how managers intuitively think about data and statistics. This article reviews a wide range of empirical results from almost a century of research on intuitive statistics. The results support four key insights: (1) Variance is not intuitive; (2) Perfect correlation is the intuitive reference point; (3) People conflate correlation with slope; and (4) Nonlinear functions and interaction effects are not intuitive. These insights have implications for the development, implementation, and evaluation of statistical models in marketing and beyond. I provide several such examples and offer suggestions for future research.