Air pressure as a function of height, p. 2: residuals from
    the simple linear regression of pressure (in mmHg) on height.
    
    -------
          [1,]        [2,]        [3,]        [4,]        [5,]        [6,] 
    145.859857  136.110876  126.361895  116.512913  107.063932   97.514951 
          [7,]        [8,]        [9,]       [10,]       [11,]       [12,] 
     88.265970   78.916988   69.668007   60.619026   51.670044   42.921063 
         [13,]       [14,]       [15,]       [16,]       [17,]       [18,] 
     34.572082   26.123100   18.074119   10.325138    2.576157   -4.872825 
         [19,]       [20,]       [21,]       [22,]       [23,]       [24,] 
    -12.421806  -19.370787  -26.319769  -39.617731  -52.315694  -64.513657 
         [25,]       [26,]       [27,]       [28,]       [29,]       [30,] 
    -75.911619  -86.609582 -130.799395 -160.789208 -178.379021 -185.168834 
         [31,]       [32,]       [33,]       [34,]       [35,]       [36,] 
   -182.458647 -171.048460 -151.638273 -125.728086  -94.817899  -60.007713 
         [37,]       [38,]       [39,]       [40,] 
     18.512661  104.833035  196.053409  290.233783 
   -----

    These residuals show a very strong convex pattern, namely they start
   out positive and decreasing, become negative while still decreasing,
   reach a minimum at the 30th residual, then start to increase, 
   eventually becoming positive and increasing. There is only one
   "turning point" where the residuals change between decreasing and
   increasing. This is very incompatible with i.i.d. residuals
   (normal or otherwise) so we'll consider other regressions.