Speaker
            
    Victor Zlokazov
        
            (JINR, LIT)
        
    Description
A significant amount of the human knowledge of Nature is based on the      
evidence which the rigorous mathematics would have called insufficient.    
However, in some cases (very important ones indeed) the increasing of data 
statistics is hardly implementable, added to which                         
once such problem has been overcome in one field of the research           
investigations there appear another ones with the same problem.            
Radioactivity is a very proliferic source of the information about the     
atomic and subatomic world, but in some cases it is just an example of     
the above situation, e.g., experiments on the synthesis of superheavy      
elements, the outcome of which is always small.                            
The report discusses the different aspects of the data analysis under      
unfavorable conditions : low statistics, incomplete observation data etc.  
and their impact on the the parameter estimation and the hypothesis        
testing which in case of the exponential distribution are very unfavorable 
to the low statistics, since here its most probable event is very far from 
the expected one.                                                          
A special attention is given to criteria for an optimum test by its        
different merits: minimal confidence interval length, maximum covering     
probability, the most "natural" interpretation, etc.
            Author
        
            
                
                
                    
                        Victor Zlokazov
                    
                
                
                        (JINR, LIT)
                    
            
        
    
        Co-author
        
            
                
                        Mr
                    
                
                    
                        Vladimir Utyonkov
                    
                
                
                        (LNR)