Herman Rubin wrote:
> The way you entered your data, I cannot get your plot into my
> reply. �However, the big error you made is assuming that the
> data should be explained by a linear process. �It obviously
> is not.
>
the �temperature records are a �LINEAR scatter of point one per year.
the data �is the record SLOPES of all the data processed by a program.
��the �question is �why would �the slope data �show �an increase until
��1922 or so �and then would be stable until 1976 �then it would
increase in �a nonlinear manner �to ��the current time. ���but in all
cases �the �temperatures �are �rising. ��if you cant �understand the
question �GO AWAY
my question was �what process could have �changed the temparature �data
�so that the BEST FIT slopes would �show this pattern
this is my DATA �and �the plot of that data ����X is the year ��Y is
the
data ���Y_Calc is a computed �LINEAR fit �of this data. �not real
useful.
I truncated the �data �to be smaller than �133 yesrs.
josephus
�input data FROM TRIAL
�44 items
�A= -12.506116926 �B= 0.006558967 slope of f(N)
���UT �16 �lt �28
INDEX year ���T-DATA ������������A+B*I ������������Ycalc-Y
���I ���X �������Y ��������������Y_Calc �����������residuals
���1 �2012 ��0.67564604 �����0.69052522 ���������-0.01487918
���2 �2010 ��0.67512411 �����0.67740728 ���������-0.00228317
���3 �2008 ��0.66179562 �����0.66428935 ���������-0.00249373
���4 �2006 ��0.64898528 �����0.65117141 ���������-0.00218613
���5 �2004 ��0.63101075 �����0.63805348 ���������-0.00704273
���6 �2002 ��0.60898221 �����0.62493554 ���������-0.01595333
���7 �2000 ��0.59069909 �����0.61181761 ���������-0.02111852
���8 �1998 ��0.57266059 �����0.59869968 ���������-0.02603909
���9 �1996 ��0.54883184 �����0.58558174 ���������-0.03674990
��10 �1994 ��0.52947211 �����0.57246381 ���������-0.04299170
��11 �1992 ��0.52751347 �����0.55934587 ���������-0.03183240
��12 �1990 ��0.50738856 �����0.54622794 ���������-0.03883938
��13 �1988 ��0.49413400 �����0.53311000 ���������-0.03897600
��14 �1986 ��0.47077725 �����0.51999207 ���������-0.04921482
��15 �1984 ��0.46964545 �����0.50687413 ���������-0.03722868
��16 �1982 ��0.44794184 �����0.49375620 ���������-0.04581436
��17 �1980 ��0.42604543 �����0.48063826 ���������-0.05459284
��18 �1978 ��0.41000618 �����0.46752033 ���������-0.05751415
��19 �1976 ��0.40278508 �����0.45440240 ���������-0.05161731
��20 �1974 ��0.41122620 �����0.44128446 ���������-0.03005826
��21 �1972 ��0.40710513 �����0.42816653 ���������-0.02106140
��22 �1970 ��0.42683548 �����0.41504859 ����������0.01178689
��23 �1968 ��0.42136534 �����0.40193066 ����������0.01943468
��24 �1966 ��0.43919953 �����0.38881272 ����������0.05038681
��25 �1964 ��0.46062146 �����0.37569479 ����������0.08492667
��26 �1962 ��0.45978338 �����0.36257685 ����������0.09720653
��27 �1960 ��0.44394761 �����0.34945892 ����������0.09448869
��28 �1958 ��0.43062317 �����0.33634098 ����������0.09428219
��29 �1956 ��0.40559441 �����0.32322305 ����������0.08237136
��30 �1954 ��0.42460882 �����0.31010512 ����������0.11450370
��31 �1952 ��0.41139084 �����0.29698718 ����������0.11440366
��32 �1950 ��0.41723675 �����0.28386925 ����������0.13336751
��33 �1948 ��0.44128608 �����0.27075131 ����������0.17053477
��34 �1946 ��0.45031527 �����0.25763338 ����������0.19268189
��35 �1944 ��0.42941434 �����0.24451544 ����������0.18489889
��36 �1942 ��0.36059908 �����0.23139751 ����������0.12920157
��37 �1940 ��0.27551560 �����0.21827957 ����������0.05723603
��38 �1938 ��0.20151958 �����0.20516164 ���������-0.00364206
��39 �1936 ��0.10792066 �����0.19204370 ���������-0.08412304
��40 �1934 ��0.06421356 �����0.17892577 ���������-0.11471221
��41 �1932 ��0.04378326 �����0.16580784 ���������-0.12202457
��42 �1930 ��-0.06633484 �����0.15268990 ���������-0.21902474
��43 �1928 ��-0.05653061 �����0.13957197 ���������-0.19610258
��44 �1926 ��-0.13714154 �����0.12645403 ���������-0.26359557
�Intercept is -12.506116926 Sigma A is 1.175600577
�slope ����is 0.006558967 Sigma B is ��������0
2011 0.006558967
MY regular plot [scatter gram]