The tests that you did in the cases, changing time periods, looking
at auto correlation etc. to you seem non trivial, but that is because you found them relevant.
Not exact matches
At that time, FICO conducted numerous studies with insurers across the country to determine whether there's a statistical
correlation between a person's credit score and the likelihood that he or she will file an
auto insurance claim in the future.
That depends on the data, so you need to look
at variance for the particular record (a side note — satellite mid-tropospheric records have higher variance than surface records, and inherently require more data to make that determination),
at auto -
correlation, the scale of trend changes, all of those, to determine whether current trends are significantly different from the past.
To test that I varied the data sources, the time periods used, the importance of spatial
auto -
correlation on the effective numbers of degree of freedom, and most importantly, I looked
at how these methodologies stacked up in numerical laboratories (GCM model runs) where I knew the answer already.
Furthermore, looking
at the original sea level point data it probably contains a bit of
auto -
correlation.
Tmin
at Barrow against changes in [CO2] and SR between 1990 and 2005, we obtain adj.R2 of 0.4, and very highly sig t - stats for dSR 11.33 p - value 4.79E - 23 and RF minus 8.17 p - value r4.33E - 14, with Durbin - Watson > 2, so no
auto -
correlations.
They both shown a highly
auto correlation of the regression residuals even
at higher orders and both time series show a step function
at the 1997 - 1998 time period.
It appears to me that
at times the difference between prediction an reality has been near the borderline of statistical significance — hence posts several years back from Lucia that the trend was «falsified» and counter posts here that a correct analysis
auto -
correlation etc puts observations back within the confidence limit.
We have the mean and variance but the is
auto correlation, that in some years is going to be highly positive, like
at start of El Niño, and right after El Niño peak we have a negative
auto correlation and then positive
auto correlation right after that.