> Axel Vogt <&email@example.com> wrote: > > josephus wrote: > > > I have some data sets ENGLAND 1729-1970, NOAA 1880-2012 ?GISS == > > > NOAA data. I even have a data set for ICE but that is not my > > > problem. > > > the problem is when I run a least squares algorithm over the data > > > set. should I change the extent, the slope increases (??). > > > the big question is WHAT KIND of PROCESSING caused the RAW DATA to > > > show irregular slopes like these > > > josephus > > > > I tried to understand you question - but I am a bit lost > > > Me, too, a bit lost. But there are lots of geostatistical > techniques to accommodate lots of less-than-obvious behaviors, > correlations, etc, e.g., google the term kriging and/or see > http://wikipedia.org/wiki/Kriging > You shouldn't be surprised seeing unexpected statistical > artifacts just using straightforward least squares. > You've probably got lots more literature work ahead of you > before deciding how best to reduce, analyze, etc your data.
No, I do not want to do that, but want to know what you do (and why only for each 2nd year?).
Anyway, here are your data, plotted in a linked Excel sheet
Roughly one can say: data have 3 periods, are always a bit oscillating. And can never be approximated by a 'line'.