Statistical significance and climate change

I am linking to a blog post on statistical significance that may help explain why I am such a skeptic on the whole “human caused warming” claim:

Here’s an excerpt:

“Which is to say that according to my real, genuine, mathematically legitimate, scientifically fabricated scientific statistical scientific model (calculated on a computer), I was able to produce statistical significance and reject the “null” hypothesis of no cooling. Therefore there has been cooling. And since cooling is the opposite of warming, there is no more global warming. Quod ipso facto. Or something.

I was led to this result because many (many) readers alerted me to a fellow named Lord Donoughue, who asked Parliament a question which produced the answer that “the temperature rise since about 1880 is statistically significant.” Is this right?

Not according to my model. So who’s model, the Met Office’s or mine, is right?

Well, that’s the beauty of statistics. Neither model has to be right; plus, anybody can create their own.”

Read on:

The post explains very clearly, at least to me, why statistical significance may not be significant at all.  Another important excerpt:

“His model, which is frankly absurd, is to say the change in global temperatures is a straight linear combination of the change in “anthropogenic contributions” to temperature plus the change in “natural variability” of temperature plus the change in “measurement error” of temperature. (Hilariously, he claims measurement error is of the order +/- 0.03 degrees Celsius; yes, three-hundredths of a degree: I despair, I despair.)”  (Bold is mine)

Proxies cannot possibly yield the accuracy required for the claims made by climate science concerning warming.  They simply lack the degree of accuracy needed.  We really can’t even measure the accuracy except in very modern times.  Perhaps if we gave the proxy to 25 unrelated scientists and had them all give their interpretation of the proxy, it would become apparent that this is not an accurate measurement.  If you lack accurate measurements, then your conclusion cannot be said to be accurate based on those measurements.  There are too many assumptions and too much use of “estimated” and proxy data to give any kind of accurate result, except by random chance.  We simply do not have the data for these types of claims.

Scientific badger

Scientific badger


One comment on “Statistical significance and climate change

  1. cranky old electronics engineer says:

    Only just encountered your blog… nice, relaxed pace reading.

    It occurs to me that attempting to use proxies to the degree (pardon the pun) of accuracy stipulated by the panicky, arm-flapping bed-wetters is akin to trying to measure the size, weight, shape, speed and heading of an ocean-going vessel by attempting to monitor (any semblance of) bow waves rippling ashore on a single, small cove beach over a thousand miles away, after some guestimated delay, while ignoring the existence of all other intervening phenomena. Their only real hinderance is their self-righteous, arrogant pride, but they would send us all to hell in a handbasket before admitting their fault.

    Pride is hardness of heart. How can such people truly be concerned with the welfare of humanity? Well, obviously, they can’t. We must look elsewhere for their hidden, true motives. As always, all deception begins with self-deception.

    Yeah, anyway, good ol’ stats… one man’s mean is another man’s Poisson (heh, heh. ;-)> Seems they Weibulled about their computer model MTBF. Guess they were counting on at least another 25 years, or at least until they’ve all retired to some tropical paradise somewhere in that magically warming ocean.

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