There should be more interpretations which are derived from data, presented by those professional analysts. The empirical rules and knowledge do help as making statistical inference in Econometrics. The approaches from classical statistical analysis make judges simply resulting from historical data. To be frank, the advantage of this analysis is the objectivity, but there is a fatal drawback. That is, it does not pay attention to some logically extra information. This paper is born for the applications of Bayesian, which has the essential characteristic of accepting subjective outlook, applying empirical rules to study unit root test on exchange rate market. Furthermore, the various distributions of data may have direct effect on the classical statistical inference we use, such as Dickey-Fuller and Phillips-Perron test. To take those defects into consideration, this paper tends not to take the assumption of disturbances in normal distribution as granted. For instance, it is quite common for us to confront the heavy-tailed distribution when studying some data of time series related to stocks and targets of investment. Hence, we will apply more generalized model to do research on Bayesian unit root test. Use the model of Schotman and Van Dijk (1991) and assuming disturbance shaped as independent student-t distribution to revise the unit root test, next, applying to exchange rate market. This is the motif of this paper.