Yes, I’m still on vacation. But I couldn’t resist a quick response to this comment (and the subsequent debate):
BBC: Do you agree that from 1995 to the present there has been no statistically-significant global warming
Phil Jones: Yes, but only just.
Both trends are clearly upwards.
Phil Jones was referring to the CRU data, so let’s start with that. If you fit a linear least-squares regression (or a generalised linear model with a gaussian distribution and identity link function, using maximum likelihood), you get the follow results (from Program R):
glm(formula = as.formula(mod.vec), family = gaussian(link = "identity"), data = dat.2009) Deviance Residuals: Min 1Q Median 3Q Max -0.175952 -0.040652 0.001190 0.051519 0.192276 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -21.412933 11.079377 -1.933 0.0754 . Year 0.010886 0.005534 1.967 0.0709 . --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for gaussian family taken to be 0.008575483) Null deviance: 0.14466 on 14 degrees of freedom Residual deviance: 0.11148 on 13 degrees of freedom AIC: -24.961
Two particularly relevant things to note here. First, the Year estimate is 0.010886. This means that the regression slope is +0.011 degrees C per year (or 0.11 C/decade or 1.1 C/century). The second is that the “Pr” or p-value is 0.0709, which, according to the codes, is “not significant” at Fisher’s alpha = 0.05.
What does this mean? Well, in essence it says that if there was NO trend in the data (and it met the other assumptions of this test), you would expect to observe a slope at least that large in 7.1% or replicated samples. That is, if you could replay the temperature series on Earth, or replicate Earths, say 1,000 times, you would, by chance, see that trend or larger in 71 of them. According to classical ‘frequentist’ statistical convention (which is rather silly, IMHO), that’s not significant. However, if you only observed this is 50 of 1,000 replicate Earths, that WOULD be significant.
Crazy stuff, eh? Yeah, many people agree.