to a Poisson probability distribution (Borgman and Resio 1982). The Poisson 

 distribution has probability density 



P(x) = ^^-|j- , X = , 1 , 2 , 3 , ... (1) 



The variable x is the number of storms per year and the parameter u is the 

 average number of storms per year in this case, and u = 78 storms/20 years or 



u = 3.9 . 



7. The Chi square goodness of fit test is used to test the validity of 

 the Poisson assumption (Miller and Freund 1977). The test is based on the 

 statistic X 

 where 



n (o. - E V 



1=1 1 



and 



. Oj^ = observed frequency of years with i - 1 storms 



E^ = Poisson expected frequency of years with i - 1 storms 



2 

 If X is small when compared to theoretical chi square values, then the 



probability that the Poisson assumption is valid will be great. Table 3 



2 

 lists the values for 0^ and E^^ and the resulting value for x^ 



Table 3 

 Chi Square Test for the Poisson Model 





Number of 

 Storms 



0. 



1 



I 3 



E. 



1 



(O. - E.)=/E^ 





 1 



»:5° 1.98 



0.525 



2 

 3 



I ■< 



l.'S, '■»« 



0.001 



4 

 5 



I ' 



l:T. ^-'^ 



0.127 



6 

 7 



\ " 



]:fo 3.08 



0.275 





X^ = 0.928 



Some of the cells have been combined in the test to minimize the impact of 

 small cell counts on the resulting statistic. The theoretical chi square 



