With Climate Journalism Like This, Who Needs Fiction?
How would you figure out whether Global Warming is real? Part 3.
Cherry picking the data
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Tag Archives: environment
Hypothesis Testing
Evidence that global warming has stopped
The conclusion:
So, in the end, the evidence that global warming has stopped is … lacking.
Thinking Globally
We have had some chilly months here in Minnesota, but ….
Earth had third warmest May on record (tie with 1998 and 2005)
The global temperature has been above average now 339 straight months (more than 28 years). The last time global temperatures were below average (February, 1985), the Chevrolet Celebrity was among the top selling cars.
The Cold and the Dark
Untitled Page
On December 8 Metro Transit added a new express
bus line to downtown Minneapolis, where I work. The northern
terminus of this bus line is about 1¼ miles from
my home. This is well within normal walking distance for me, and there are sidewalks along Rice Street, where traffic can be quite serious. So
I decided it was time to leave the car at home and do my normal commuting entirely by walking and public transportation like
mia_mcdavid and I did in Chicago until 1987. I have been doing so ever since.
This has both pros and cons:
Scientific “Disagreement”
From NASA
Bayesian Probability
Back in 1976, when I got an M.S. in Statistics from Stanford, the dominant interpretation of probability and statistics was the Frequentist view. The alternative Bayesian interpretation was definitely a minority position.
In recent decades the Bayesian view has been gaining ground, especially after the spectacular success of one of its practioners, Nate Silver, in predicting the results of the 2012 U.S. Presidential election. Silver has written an excellent book, The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t, about forecasting. He gives some vivid examples of Bayesian methods.
The main point of Silver’s book is quite clear in the title: Real world data is full of noise. All too often people see some random fluctuation in the data and think that it represents some real pattern. Silver gives examples from many fields, including sports, the stock market, earthquakes, politics, and economics, that show this. In other cases, e.g. weather forecasting and climate change, there is a discernable signal in all of the noise. Silver neatly debunks some of the bad statistical methods used by the deniers of global warning.
Another good book about Bayesian probability is From Cosmos to Chaos: The Science of Unpredictability, by by Peter Coles. Coles assumes a little more comfort with mathematical notation than Silver, but the actual arguments do not require more than algebra. While discussing the history of probability theory from its roots in gambling, he concentrates on physics and astronomy, which also contributed significantly to the development of statistics. He is a strong advocate of Bayesian probability and suggests the Bayesian view avoids some nasty issues in the interpretation of statistical mechanics and quantum mechanics, notably that in
the latter subject there is no reason for the Many Worlds Interpretation. Incidentally, he has also argued that the conventional interpretation of Sherlock Holmes is wrong. See The Return of the Inductive Detective.
The Frequentists vs. Bayesian debate has also made Xkcd. The implication is that some level we are all Bayesians, even if we don’t admit it.
On an issue in reasoning with probabilities, Ethan Siegel discusses the Inverse gambler’s fallacy in The Last Refuge of a Science-Denying Scoundrel.
From Hilbert Space to Dilbert Space, and beyond 