A CRITIQUE OF THE BODY-SURFACE LAW. 



175 



Confining our attention to the four general series, IV-VII, in which 

 the number of individuals is reasonably large, it is apparent that in 

 every case prediction from the linear equations based on body-surface 

 as determined by the Du Bois height-weight chart gives lower average 

 deviations with regard to sign than do those based on either body- 

 surface by the Meeh formula or body-weight. Thus the Du Bois 

 height-weight chart gives the best prediction, in so far as accuracy of 

 prediction can be measured by the average deviation of the predicted 

 from the actually observed value. There seems to be little difference 

 between the results of prediction from body-weight and from body- 

 surface as estimated by the Meeh formula. 



TABLE 67.- Average deviation without regard to sign of total heat-production as predicted 

 by linear equations from actual heat-production. 



Turning to the average deviations without regard to sign, we note 

 from table 67 that in the whole series of 64 individuals the three 

 methods give deviations of only 109, 108, and 97 calories or stand in 

 the ratio 6.64 : 6.57 : 5.93 per cent. Thus the difference in the per- 

 centage error of predicting from body-weight and body-surface by 

 the Du Bois height-weight chart is only 6.645.93=0.71 per cent. 



For the 72 individuals of the Gephart and Du Bois selection the 

 average deviations for the three methods of prediction are 88.1, 87.4, 

 and 88.7 calories, or stand as 5.43 : 5.38 : 5.46 per cent. Thus body- 

 weight is a little better than body-surface by the height-weight chart 

 as a basis of prediction. In the two feminine series the absolute error 

 in calories is considerably larger, the percentages ranging from 6.87 

 to 11.21. In both feminine series the Du Bois height- weight chart 

 gives the lowest and body-weight the highest average deviation. The 

 height- weight chart is therefore the best and body- weight the worst 

 basis for prediction. 



