Could eating too much margarine be bad for your critical faculties? The “experts” who so confidently advised us to replace saturated fats, such as butter, with polyunsaturated spreads, people who presumably practise what they preach, have suddenly come over all uncertain and seem to be struggling through a mental fog to reformulate their script.
Joanna Blythman summarizes all that is dodgy about current nutritional advice both here and in the UK.
It’s not just butter vs margarine, either. Red meat, salt, and eggs have been slandered, while the government emphasis on cereals and grains appears increasingly to have been a conspiracy to keep us fat and stupid.
The crucial phrase “avoid processed food” appears nowhere in government nutritional guidelines, yet this is the most concise way to sum up in practical terms what is wholesome and healthy to eat. Until this awareness shapes dietetic advice, all government dietary guidance should come with a tobacco-style caution: Following this advice could seriously damage your health.
Amen, Sister, to the advice on processed foods. A quick read of their ingredients (sugars, flour, and some kind of cheap grease) should be sufficient to put you right off them.
Tip from Gary Jones.
That question gets asked dozens of times every semester in my statistics classes; it’s pretty clear that most of my students have no sense of scale or proportion about numbers.
But now I have Dr Rhett Alain’s short answer in his Dot Physics Measurement and Uncertainty Smackdown, wherein he refers to the (extremely) long answer in John Denker’s excellent Uncertainty as Applied to Measurement and Calculation. Why we’re not teaching this in our service courses for science majors, I have no idea. The Monte Carlo approach described by Alain is a simple application of what statisticians call “bootstrapping,” so perhaps I will start.
Second hand tip from the Geek Press
More and more of all this hippy-dippy green energy bullshit we’re saddled with is turning out to be a collection of Really Bad Ideas:
The only upside I see is that some of our more obnoxious greeny hipsters will tool around town on their BikeShare bikes and get clocked by some drunk in an SUV.
My students repeatedly ask about setting the critical values or interpreting p-values in statistical hypothesis testing. My stock answer is they should do their tests at the 5% level, since this is the most common and accepted practice in the biomedical community (my translation: it’s what all the KooL KiDz do.)
But now some upstart Bayesian Aggie (who’s only published 122 papers) has taken a closer look at p-values and significance levels, and claims the critical values are too loose, and need tightening up. Good-bye 5%, hello 0.5% (for slackers) or 0.1% (for “real” researchers). I suspect this would eliminate entire forests of bullshit journal articles with p-values of 0.05 minus epsilon, and otherwise wreak havoc in academia.
My only grumble is that I need bigger samples for many of my teaching examples. I just wrote up a neat demo of the Breusch-Pagan test for homoskedasticity, which rejected with a p-value of 0.0308. That ain’t gonna cut it in the New World of Your-Evidence-Ain’t-Good-Enough World Order. #@$*&++@#!, twice.
Tip from Briggsy, the Bayesian Bomb-Thrower.
What he said. Read the whole thing,
I especially enjoyed the discussion of evolutionary biology. Personally, I think the field is pure bunk. My favorite question for eBiologists is “What were the evolutionary pressures that modified dogs so that they all enjoy riding in cars with their heads out the window? Does it go back to Dino riding around with Fred Flintstone?”
Tip from William M. Briggs, Statistician to the Stars.
This is just mean, but it couldn’t happen to a more deserving band of grifters.
Tip from the Instapundit, who says APPLY NOW.