© Springer International Publishing Switzerland 2014. Bias, confounding, and random variation/chance are the reasons for a non-causal association between an exposure and outcome. This chapter will define and discuss these concepts so that they may be appropriately considered whenever one is interpreting the data from a study. Several types of common bias will be discussed (e.g. measurement bias, sampling bias, etc.) and effect modification (interaction) will be explained.