Observational studies entail making several decisions before data collection, such as the observational design to use, the sampling of sessions within the observational period, the need for time sampling within the observation sessions, as well as the observation recording procedures to use. The focus of the present article is on observational recording procedures different from continuous recording (i.e., momentary time sampling, partial and whole interval recording). The main aim is to develop an online software application, constructed using R and the Shiny package, on the basis of simulations using the alternating renewal process (a model implemented in the ARPobservation package). The application offers graphical representations that can be useful to both university students constructing knowledge on Observational Methodology and to applied researchers planning to use discontinuous recording in their studies, because it helps identifying the conditions (e.g., interval length, average duration of the behavior of interest) in which the prevalence of the target behavior is expected to be estimated with less bias or no bias and with more efficiency. The estimation of frequency is another topic covered.