Likert-type data are often assumed to be equidistant by applied researchers so that they can use parametric methods. Since this rarely is tested, the validity of parametric analyses of Likert-type data is often unclear. This paper consists of two parts where the authors deal with this validity problem in two different respects. In the first part, the authors use an experimental design to show that the perceived distance between scale points on a regular five-point Likert-type scale depends on how the verbal anchors are used. In the second part of the paper, the authors use Monte Carlo simulations to explore how parametric methods commonly used to compare means between several groups perform in terms of actual significance and power when data are assumed to be equidistant even though they are not. The results show that the preferred statistical method to analyse Likert-type data depends on the nature of their nonequidistance as well as their skewness.