Experimental designs for functional magnetic resonance imaging (fMRI) experiments can be characterized by their estimation efficiency, which is a measure of the variance in the estimate of the hemodynamic response function (HRF), and their detection power, which is a measure of the variance in the estimate of the amplitude of functional activity. Previous studies have shown that there exists a fundamental trade-off between efficiency and power for experiments with a single trial type of interest. This paper extends the prior work by presenting a theoretical model for the relation between detection power and estimation efficiency in experiments with multiple trial types. It is shown that the trade-off between efficiency and power present in multiple-trial-type experiments is identical in form to that observed for single-trial-type experiments. Departures from the predicted trade-off due to the inclusion of basis function expansions and the assumption of correlated noise are examined. Finally, conditional entropy is introduced as measure for the randomness of a design, and an empirical relation between entropy and estimation efficiency is presented.