The formulae advanced by Popper to calculate the degree of corroboration C of a scientific hypothesis are unsatisfactory in that the probability values required in the computation are often not available. An attempt is made to define a quantitative measure B* in the place of C in which only countable empirical values would be used. This condition is fulfilled in two basic formulae and eq. ), which could be applied to calculate the degree of corroboration. When m successful falsifications of (...) the hypothesis h appear after a sequence of n unsuccessful ones, the pragmatic degree of corroboration B* results from the difference between B and the analogue value of the falsification F* and eq. ). In the event that the hypothesis can be "rescued" through a correction, increased experimental effort must be made with the revision. This would be taken into account through the correction equation ). When the hypothesis cannot be corrected, however, it can no longer exceed the value of 1-F*, even after numerous verification experiments. In the process of deciding whether a hypothesis is "adequately" verified or falsified, a lower threshold ${\rm B}_{{\rm u}}$ und Bₒ must be selected. These values have to be chosen on an intuitive subjective basis. The same applies to the strength of unsuccessful falsifications . This evaluation is expressed by a multiplicative constant a̱ ) or an additive constant kₐ in eq. . Despite the subjectivity of the values a̱, kₐ necessary for the calculation of B*, and of the values ${\rm B}_{{\rm u}}$ , Bₒ for the decision to discontiue the examination of the hypothesis, I feel that amongst the scientists within a particular field of research, a consensus for these values should be possible. Through a quantitative determination of B* the procedure for testing a hypothesis, considered to be a closed loop process, becomes clearer. To estimate the values of B* could not only have an influence upon the decisions of the respective researchers or research groups examining a hypothesis, but also be of assistance in decisions regarding research grants when financial resources are limited. (shrink)