Choosing the sample size is a problem faced by anyone doing a survey of any type. ‘‘What
sample size do we need?’’ is one of the most frequently asked questions of statisticians.
The answer always starts with ‘‘It depends on...’’. In this paper, we respond to this question
by considering two criteria, total cost of experiment and mean squared prediction error
in prediction problem. Towards this end, we discuss the problem of Bayesian predicting
future observations from an exponential distribution based on an observed sample, when
the information sample size is fixed as well as a random variable. Some distributions for
the information sample size are considered and then for each case we find the parameter of
distribution of the information sample size, such that the point predictor of a future order
statistic has minimum mean squared prediction error when the total cost of experiment is
bounded. To show the usefulness of our results, we present a simulation study. Finally, we
apply our results to some real data sets in life testing.