If equation (3) is fitted to individual years of data, the 

 analysis provides in /3 an estimate of the yearly average of 

 the surface temperature. The sequence of /3 's can be ex- 

 amined for the existence of trend in the time series. Testing 

 for trend using either the theory of runs or the autocorrelation 

 coefficient with lag unity indicates that no long term trend 

 exists in any of the time series under consideration. Details 

 of the trend analysis will be presented in a subsequent 

 report. 



MISSING DATA 



The six locations have data missing in amounts varying 

 from 2 percent to 40 percent of the number of possible 

 observations. Intuitively it would seem that, for the types 

 of analyses attempted, a fairly large fraction of randomly 

 distributed missing data can be tolerated. It is the purpose 

 of this report to examine quantitatively the effect of various 

 fractions of missing data. 



Although the expression missing data has been 

 used thus far in the discussion, it is worthwhile now to 

 comment on this usage. Conceivably, in a statistical prob- 

 lem, missing data can result in nothing more drastic than a 

 sample of smaller size than planned. This might well be 

 the case in a regression analysis in which the residuals are 

 independently distributed with equal variances, and the 

 missing data are uniformly or randomly distributed through- 

 out the ranges of the independent variables. On the other 

 hand, missing data in an extreme case can invalidate an 

 experiment. 



15 



