Transactional Memory (TM) is an attractive concurrency control mechanism that should deliver much better performance than locks in case when transaction conflicts are rare. But, if the probability of conflicts is high, TM program performance may be very poor. Therefore, when engineering mission critical systems, we need to be able to calculate conflict probabilities. In this paper we study a class of stochastic TM programs for processing groups of transactions on a set of shared t-variables, e.g. bank accounts. Individual transactions are selecting variables they are operating on uniformly at random. We identify and define various types of conflicts among transactions that may arise in such circumstances. We also show how to calculate probabilities of various types of conflicts on some simple examples of groups of transactions sharing one or two t-variables. Our work is still in progress, but the results shown here are affirmative for the approach we use, and they stimulate further research towards more general analysis of this class of TM programs.