Study quality depends on a number of factors, one of them being internal validity. Such validity can be affected by random and systematic error, the latter also known as bias. Both make it more difficult to assess a correct frequency or the true relationship between exposure and outcome. Where random error can be addressed by increasing the sample size, a systematic error in the design, the conduct or the reporting of a study is more problematic. In this article, we will focus on bias, discuss different types of selection bias (sampling bias, confounding by indication, incidence-prevalence bias, attrition bias, collider stratification bias and publication bias) and information bias (recall bias, interviewer bias, observer bias and lead-time bias), indicate the type of studies where they most frequently occur and provide suggestions for their prevention.