ABSTRACT
The majority of experiments in biomedicine and other health-related sciences involve mathematically formalized tests. The common goal in testing is to employ appropriate and efficient statistical procedures to make informed decisions based on data. The aim of the scientific method in decision theory is to simultaneously maximize quantified gains and minimize losses when reaching a conclusion. In order to correctly define statistical testing procedures and interpret the corresponding results, practitioners should research the nature of clinical data, experimental limitations, and instrumental sensitivities, as well as appropriate state objectives and their corresponding hypotheses. In clinical studies, researchers collect and analyze data with the goal of soliciting useful information. One of the first critical components of the data analysis procedure is data collection and entry. This is the process where the raw data are checked for accuracy and subsequently cleaned.
