we 
 introduce a step transition and state identification ( stasi ) 
 method for piecewise constant single - molecule data with a newly derived 
 minimum description length equation as the objective function . 
 we 
 detect the step transitions using the student s t test and group the segments into states by hierarchical clustering . 
 the optimum number of states is determined based on the minimum description 
 length equation . 
 this method provides comprehensive , objective analysis 
 of multiple traces requiring few user inputs about the underlying 
 physical models and is faster and more precise in determining the 
 number of states than established and cutting - edge methods for single - molecule 
 data analysis . 
 perhaps most importantly , the method does not require 
 either time - tagged photon counting or photon counting in general and 
 thus can be applied to a broad range of experimental setups and analytes .