We are a commune of inquiring, skeptical, politically centrist, capitalist, anglophile, traditionalist New England Yankee humans, humanoids, and animals with many interests beyond and above politics. Each of us has had a high-school education (or GED), but all had ADD so didn't pay attention very well, especially the dogs. Each one of us does "try my best to be just like I am," and none of us enjoys working for others, including for Maggie, from whom we receive neither a nickel nor a dime. Freedom from nags, cranks, government, do-gooders, control-freaks and idiots is all that we ask for.
In a marathon session yesterday, politicians allowed people from Newtown and various other lobbying organizations to state their views about guns. Several of the more emotionally compelling statements made the press and have been forced on an unsuspecting public, as a means to push harsher gun control laws. One statement in particular struck me as I watched the news this morning. Susie Ehrens, whose daughter survived the attack, made the following plea:
“We stop being the world’s greatest country when we allow our most vulnerable citizens to be slaughtered because we might offend people by taking away their guns. We stop being something to be proud of when we love our guns more than we love our children.”
It is heartfelt sentiment with a strong statement. I have no doubt many people, many parents in particular, were moved closer to supporting gun control as a result. Certainly, it is a statement which hit me hard - do I really love guns more than I love children? So much so that I'm willing to let children die just because I support the freedom to bear arms?
Of course not. After thinking about this statement, I believed a response was needed. Mainly because it is factually inaccurate, at least in terms of how it describes me, and it is logically flawed, in general.
I've discussed the Gambler's Fallacy in the past (eg if you flip nine heads in a row, what are the odds the next toss will be a tail?). The inverse is another matter. Wiki gives this example:
Suppose a man walked into a room and saw someone rolling a pair of dice. Furthermore, imagine that the result of this dice roll is a double-six. The man entering the room would commit the Inverse Gambler's Fallacy if he said, "You've probably been rolling the dice for quite a while, since it's unlikely you would get a double-six on your first attempt."
The author points out that we all know that "correlation does not indicate causation", but there is an equally important error often drawn from data: The confusion of statistical significance with real world meaning.
As science grows more powerful and government more technocratic, the stakes of correlation—of counterfeit relationships and bogus findings—grow ever larger. The false positive is now more onerous than it's ever been. And all we have to fight it is a catchphrase.
"If you want a happy ending, that depends, of course, on where you stop your story."
Orson Welles
And on where you start it. We may not be professional scientists here on the Farm, but we've all read the classicHow to Lie with Statistics, and I assume we've all studed at least basic calculus.
(And we all also know that computer modeling depends on the parameters you chose, or adjust ex post facto: "With four parameters I can fit an elephant, and with five I can make him wiggle his trunk." - John Von Neuman. In science, if data fails to fit models, they adjust the models to fit the data, and keep their jobs and federal grants. In finance, you get fired or lose your bonus.)
Sticking with Orson Welles for today, my point is elementary math: If you select your end point (and your starting point), you can extrapolate out any line from any piece of any graph or curve you want. That's termed "cherry picking." That's why they say that, if you extrapolate the curve of the log graph of the population of Houston from 1950 to 1980, Houston would shortly contain the entire population of the USA.
Climate alarmists are famous for extrapolating from small, selected pieces of data - and also for continual realignment of modeling parameters (which is not science, it's computer gaming).
Let's accept that post-glacial global warming has been going on, with dramatic bumps up and down but generally beneficially for humans (not for Wooly Mammoths), for 10,000 years, with the resulting 120-150 meters of ocean rise. (There are many Neolithic villages underwater in the English Channel and the North Sea, many Indian villages underwater 50-60 miles out from the coast of Virginia, etc.) This will continue until the climate tide changes back to the next glaciation in the next few centuries or millennia. Given recent predictions, we are warned to expect at least several decades of global cooling around now. Will it be the Big One? A warning to go long Key Largo real estate?
Global warming has raised global sea level about 8 inches since 1880, and the rate of rise is accelerating. Rising seas dramatically increase the odds of damaging floods from storm surges.
As if it all began in 1880. It's probably closer to 6 inches in the past 200 years, but let that pass. The real question is why they picked 1880 instead of saying "Rising seas since 1800 increase the risk of damaging storm surges"? The line would be less scarey. Or better yet, why not say "Rising seas since 15,000 BC increase the risk of damaging storm surges"? Look at this graph. Why not draw your average beginning at 1800?
Aha. they picked a low point and a high point on the curvacious historical graph, and are extrapolating from that teensy piece of it to instill terror. If you picked 1800 as your starting point, your line would look different.
And, as we posted yesterday, if you picked 18,000 years ago, your take on the data would be quite different again. You would relax and turn on the basketball game. Go Huskies - and we may need real Huskies here soon:
Call me paranoid if you want, but my view is that there is an unspoken alliance (not a conscious conspiracy) between greedy scientists and greedy governments of all sorts to make a big deal out of a big nothing. I hope to survive the big chill to see that finally people will have admitted, as they finally admitted about the imminent Ice Age scare of the 1970s - that it is pure hype.
But, what the heck, let's step even further backwards from the frame for the really Big Picture. I'll bet teacher never told you that we remain in a cold spell, historically-speaking. Yes, indeed. Polar ice caps are not normal for planet Earth. The earth doesn't have a fever - it has a very bad cold right now:
It depends on how you define "thinking." If "thinking" means an effort to form a logical progression of thoughts and ideas, words sure come in handy whether you intend to communicate the thoughts or not. In my experience, most people tend to avoid the effort that this requires unless they are trained to do it in some area of life such as diagnosing a car breakdown or a legal case or a medical complaint.
But if "thinking" refers to all sorts of mental activities, then of course words are not required for most of it. Impulses, gut feelings, images, daydreams, movement, musical ideas, etc. are all wordless mental activity (I exclude mathematics, which is just another language). Furthermore, unconscious mental activity, which may be the bulk of mental activity, is all or mostly wordless.
Speaking only for myself, I find that my words and my thought stream seem to do a sort of dance together, and a fresh new word or verbal concept can add new color or shape to it all. What is most fun is when a fresh word or phrase or concept crystallizes a dimly-thought thought.
People of all stripes will go to lengths to hold onto their preferred views of things. Re-thinking is difficult and often upsetting to one's equilibrium. But facing reality generally is more effective in life - however painful at times. Upsetting a comfortable equilibrium can also sometimes lead to better things, open up new vistas.
Dr. Sanity has a detailed essay on the topic: DOES THE LEFT UNDERSTAND PSYCHOLOGICAL DENIAL? Even if you overlook the political aspects of her essay, it's a good overview of the points at which psychological defenses and logical error frequently intersect.
We have rreported so many scientific frauds in the past couple of weeks, I thought I would highlight some commonly-used "data-management" tricks designed to dishonestly influence people.
1. "Clustering." We have all heard about cancer clusters - Why does my town have triple the breast cancer of towns two miles away? There must be someone I can sue about this. Such claims have an emotional appeal, but they are nonsense. Random distribution is not even - it is uneven. Just try flipping a quarter, and you will get little runs of tails. Clustering is a natural effect of randomness, but trial lawyers are always busy trying to track them down: they can get rich before anyone figures out the game.
2. "Cherry-picking." Cherry-picking is a frankly dishonest form of data presentation, often used by newspapers to create alarmist stories about the economy, the environment, food safety, etc. It fools people without some decent science education. What it entails is combing through, say, 60 pieces of data, and then using the three points that support your argument, and ignoring the rest. Presenting random changes as meaningful facts is a lie. Environmentalists use this all of the time, as do other agenda-driven fact-handlers. A casual use of this fallacy is characteristic of The New York Times typical headline: Despite Good Economic Statistics, Some Are Left Behind - and then they scour NYC to find some single black mom in the Bronx who cannot support her kids - and she becomes the "story".
3. "Anectdotal evidence." The above example could also be termed "anectdotal evidence." If you look around, you can always find an exception, a story, and example - of ANYTHING. But anectdotes are compelling, and Reagan used them to the best effect. And how about those swimming Polar Bears! (I always thought they liked to swim.)
4. "Omitted evidence". You tell me how common this is! A first cousin of Cherry-picking, Omitted Evidence is also a lie. All you do is ignore the evidence and data that disagrees with your bias or your position. Simple.
5. "Confirmation bias". People tend to remember evidence which supports their opinion, belief, or bias, and to dismiss or forget evidence which does not. It's a human frailty. Humans have to struggle to be rational.
6. "Biased Data". "A poll at a local pre-school playground in Boston at 2 pm today indicated that 87% of likely voters will vote for Obama." Picking your data sources, like picking the questions you ask, can determine your results with great accuracy. As pollsters always say, "Tell me the answer you want, and I will design the question."
7. "Data mining." Data-mining is used by unscrupulous academics who need to publish. Because it is a retroactive search for non-hypothesized correlations, it does not meet criteria for the scientific method. Let's say you have 10,000 data points from a study which found no correlation for your hypothesis. Negative correlation studies are rarely published, but you spend a lot of time collecting it - so you ask your computer if it can find any other positive correlations in the data. Then you publish those, as if that was what you had studied in the first place.
Image: two good varieties of cherries for picking; Stella on the left, Lapins on the right, from Miller Nurseries
A former intern at my office is now working with this speaker and directed me to this presentation. It's a fascinating discussion of choice. Recently, there was a post on Maggie's about the Runaway Boxcar. How do we approach choice in a crises? Stress alters how we make choices, as well as how we view them. So, too, does culture. At times, the speaker in this video criticizes American views of, and approaches to, choice. It is unfortunate, because the entire presentation is wonderful. She points out Americans could benefit by incorporating more collaborative approaches to choice, as opposed to the highly individualistic view we tend to have. But she fails to mention other cultures lack the insight the American perspective has, and could benefit from more choice, rather than less. It is also worth noting that the American perspective allows for greater collaborative approaches to choice, whereas other cultures tend to look down on individualistic views.
Choice is difficult. Choices can, at times, be paralyzing. But it doesn't mean that more choice is always the answer or that the American narrative on choice is wrong. It just means the American narrative of choice is different, and that American history shows more choice may not be better, but yields better overall results.
And, honestly, I can tell the difference between Coke and Pepsi. They have very distinct and different tastes. Coke is better (to me).
This past weekend, my elder son asked me to drive him to the outlets so he could get some Ralph Lauren shirts at a reduced cost. Frankly, I don't know where he got this penchant for name brand clothing, but it's his money, not mine. What is my money is the gas it takes to drive an hour to the outlets and the time I gave up to make the 2 hour (round trip) drive. I thought it would be a good lesson for him on 2 levels. First, I could teach him about opportunity costs by showing him why the trip was frivolous. Second, he'd get some driving practice so he could get his license in 2 weeks.
I wound up getting to fulfill my goals, he got his shirts, and we both learned a valuable lesson.
No good deed goes unpunished. In other words, Murphy was right. You can almost count on unintended consequences.
Whether the "research" is about medicines, climate, sociology, or whatever, greedy human nature always finds a place for itself. This is why we, at Maggie's, always assume a skeptical posture towards "studies."
Most "studies" show that researchers want to get money and jobs for doing studies.
In the past year, we have been overwhelmed with the sleaziness of the warmist crowd and the social psychology crowd, but today we find pay to play in university education research.
Almost everybody has an agenda, even scientists. It's human. That's why we remain skeptics about everything. Call it cynical if you want, but we think it's being realistic.
What the researchers omitted, as they went on to explain in the rest of the paper, was just how many variables they poked and prodded before sheer chance threw up a headline-making result—a clearly false headline-making result.
The odds of statistical bogosity grow when researchers don't have to report all the ways they manipulated their data in exploratory fashion. For example, the researchers "used father's age to control for baseline age across participants," thereby fudging the subjects' actual ages. They factored in lots of completely irrelevant data. And, rather than establish from the outset how many subjects they would test, they tested until they obtained the false result.
The authors of that provocative paper were Joseph P. Simmons and Uri Simonsohn of the University of Pennsylvania, and Leif D. Nelson of the University of California at Berkeley. "Many of us," they wrote—"and this includes the three authors of this article"—end up "yielding to the pressure to do whatever is justifiable to compile a set of studies that we can publish. This is driven not by a willingness to deceive but by the self-serving interpretation of ambiguity. ... "
An RCT is a "randomized controlled clinical trial."
We have discussed the scientific fallacy of "data mining" here in the past in which, instead of testing an hypothesis (aka the Scientific Method), the researcher simply asks the computer to find any correlations in the mountain of collected data. That is not science. This is typically done when a researcher has a mound of data which did not support his hypothesis. So as not to waste it, he asks the computer to find something else in it.
In any mountain of data, some correlations can be found if only by laws of randomness - see the legal hoax of so-called Cancer Clusters.
Often enough, when you read "Study says...", you are reading a report from data mining. Our readers know that a statistical correlation often - or usually - means nothing, but data-mining "information" is non-information. Generally speaking, newspaper reporters never passed Statistics 101. (I did, but found stats difficult to explain to innumerate juries who even get confused by basic algebra.)
Even medical professionals get taken by this growing technique. It's most common when secondary studies use the database from participants in a randomized controlled trial to look for correlations not to scientifically test a hypothesis, let alone one the original trial had been designed to fairly test. Carefully controlled clinical trials are concerned with causes and effective treatments. In contrast, multivariate analyses of large databases, with their statistical manipulations and regression computer modeling, are statistics. Statistics is about correlations. It's not biological research.
However, the science is settled (via Watts): there is probably or possibly a short-term (centuries) warming trend, if the data is worth anything (about which I am a skeptic). Nothing to think twice about unless you plan on bringing farming back to Greenland in 300 years:
Note the dramatic correlation with global CO2 emissions! None. Here's a better correlation which shows some real proof: Global temperatures caused by decrease of Mediterranean pirates.
QED - it's a linear inverse relationship This cause is therefore settled science, and the obvious solution to refrigerate ourselves is to import more pirates into the Med until we are cold enough.
Who could have anticipated that? Taxpayers bribe people to live in flood zones. Brilliant! For total stupidity, NOLA is not even a flood zone - it is permanently below sea level, and always has been. Why am I, who made the reasonable decision to live above sea level, responsible for the life choices of people who want to live underwater?
And, of course, flood zones and flood plains are basically "wetlands." One might think these places should be protected from development for environmental and flood control reasons. A farm? OK, if you understand that it will periodically get flooded while being delivered a good supply of fresh, healthy silt for your next crop.
I know about flood zones. Part of our property is in one. We keep it in horse pasture, and our pool is down there. House and barns are above. People in 1786 weren't stupid, and they did not expect the government, ie their neighbors, to protect them from nature.
Furthermore, if you believe Al Gore that the water is rising, perhaps we should be bribing people to move further from water...but nobody believes Al Gore anymore.
The alarmists are playing whack-a-mole with any data which does not fit their hypotheses and predictions. This is the stuff of politicians, children, and litigators, not scientists.
One definition: An error in reasoning in which one assumes that the observed relationship between current events and some historical events represents a causal relationship.
Such reasoning is not consistent with the scientific method. When data don't fit your hypothesis, you can't makes excuses for your data while leaving your hypothesis unchanged.
If you play that game, you also violate the rules of Falsifiability by making a non-falsifiable hypothesis. My bold:
(Karl Popper) A conjecture or hypothesis must be accepted as true until such time as it is proven to be false. Popper maintains that scientists approach the truth through what he calls "conjecture and refutation." In actuality, scientists approach the truth not through conjecture and refutation, but through conjecture and CONFIRMATION, i.e. demonstration, by means of careful experiment, that a hypothesis corresponds to the facts of reality. Until the phenomenon is proven TRUE there is no obligation to base my attitude toward it on the assumption that it MIGHT be true. If there were such an obligation, then I would be obliged to give serious consideration to every crackpot notion that has ever been put forward.
If an hypothesis cannot be refuted by data, it's not science: it's a belief system. The evidence that there has been no warming for over a decade is difficult data indeed in light of their hysterical predictions, so now they have invented covert warming. This is pathetic and embarassing. Tweaking computer models to fit unexpected data is not science. It's overt fudging.
As a commenter at Watts pointed out, with some math adjusting you can prove Ptolemy's solar system to be an accurate model.
What... emerges from this is a convenient flexible device to explain any climate change and blame it on humans. Is there warming? Its caused by CO2. Cooling? It can only be smokestack particles.
Honest discussions or debates have one purpose: to illuminate a subject with facts and theories which relate facts to eachother, and perhaps to persuade. Dishonest debates or arguments are really just fights with words, and of interest only to litigators and politicians.
Fallacious arguments of the false assumption type are used in both: in the former by accident or out of ignorance, and in the latter as a tactical trick (eg "If the glove don't fit, you must acquit.").
When questions are posed in that manner, they are known as loaded questions. They are "loaded" with an effort to seek your acquiescence to an unspoken assumption. (The classic is "When did you stop beating your wife?") The correct response to questions with hidden assumptions is to point that out, and to challenge the hidden assumption. Otherwise, you will fall into a trap.
When engaging on an issue, always examine the other guy's assumptions first, because a topic can go nowhere with fallacious assumptions, and there can be no constructive discussion if you do not accept the other guy's premise. In that case, you must address the premise first, backing up before you can move forward.
Here are some simple examples of fallacious assumptions. Usually, in arguments, the assumptions are unstated, "assumed." It's better to state them first just as one lists one's "givens" in geometry proofs. Sometimes, just addressing the assumptions clears everything up.
I have been neglecting my Fallacy portfolio here at Maggie's for quite a while. My bad.
Category Error is not a complex notion, but it was formulated in a somewhat complex way by the brilliant Gilbert Ryle in his classic work, The Concept of Mind (this via Wiki):
The term "category-mistake" was introduced by Gilbert Ryle in his book The Concept of Mind (1949) to remove what he argued to be a confusion over the nature of mind born from Cartesianmetaphysics. Ryle alleged that it was a mistake to treat the mind as an object made of an immaterial substance because predications of substance are not meaningful for a collection of dispositions and capacities.
Specifically, the phrase is introduced in chapter 1, section 2. The first example he gives is of a visitor to Oxford. The visitor, upon viewing the colleges and library, reportedly inquired “But where is the University?"[1] The visitor's mistake is presuming that a University is part of the category "units of physical infrastructure" or some such thing, rather than the category "institutions", say, which are far more abstract and complex conglomerations of buildings, people, procedures, and so on.
Ryle's second example is of a child witnessing the march-past of a division. After having had battalions, batteries, squadrons, etc. pointed out, the child asks when is the division going to appear. 'The march-past was not a parade of battalions, batteries, squadrons and a division; it was a parade of the battalions, batteries and squadrons of a division.' (Ryle's italics)
His third example is of a foreigner being shown a cricket match. After being pointed out batsmen, bowlers and fielders, the foreigner asks: 'who is left to contribute the famous element of team-spirit?'
He goes on to argue that the Cartesian dualism of mind and body rests on a category-mistake.
Yes, I think it does. But... I think, therefore I post things at Maggie's Farm. From another site, here's a simple formulation of this common and basic fallacy:
These fallacies occur because the author mistakenly assumes that the whole is nothing more than the sum of its parts. However, things joined together may have different properties as a whole than any of them do separately. The following fallacies are category errors:
Composition (Because the parts have a property, the whole is said to have that property)
Division (Because the whole has a property, the parts are said to have that property)
Give us some solid examples. I don't have time think up some good ones today. Duty before pleasure.
What flows into you from the myth is not truth but reality (truth is always about something but reality is about which truth is) and therefore every myth becomes the father of innumerable truths…
I could write, and run in circles, on this topic for days. So I won't. Plus I promised She Who Must Be Obeyed that I would clean up the kitchen. Fact.
True � The statement is accurate and there�s nothing significant missing. Mostly True � The statement is accurate but needs clarification or additional information. Half True � The statement is accurate but leaves out important details or takes things out of context. Barely True � The statement contains some element of truth but ignores critical facts that would give a different impression. False � The statement is not accurate. Pants on Fire � The statement is not accurate and makes a ridiculous claim.
In the political world, there are all sorts of truth. In the real world, only one sort. In the real world, a half-truth is a lie.
I guess we don't have to worry about that baloney. I was hoping a good one would hit up here, so I could have an excuse for a day or two off work to catch up on my chores. We know how to deal with bad weather.
Globalistical warmening fails again. Funny how negative results never make headlines or get attention. Even important negative findings in science have trouble getting published in scientific journals. There must be a fallacy term for that, but I'm not sure what it is. If a good hurricane hit land this year, the Al Gore folks would be all over it.
What am I smoking? A Griffin corona. Nice. No, actually, it's not a corona. It's bigger than that. Tasty, whatever the Griffin is that I bought from my local upscale cigar store Indian.
"Bridge of asses." Donkeys do not like to cross bridges.
In mathematics, the term is applied to the problem from the first book of Euclid that if two sides of a triangle are equal then the angles opposite those sides are also equal.
Traditionally, the bridge of asses referred to Euclid's Fifth Theorem of planar geometry, the comprehension of which and the implications of which were and are a sticking point for less-bright students.
By the way, this is a good if somewhat challenging book: Experiencing Geometry. A bit of a pons asinorum itself.
We have rreported so many scientific frauds in the past couple of weeks, I thought I would highlight some commonly-used "data-management" tricks designed to dishonestly influence people.
Whether the "research" is about medicines, climate, sociology, or whatever, greedy human nature always finds a place for itself. This is why we, at Maggie's, always assume a skeptical posture towards "studies." 
A perfect example of it: 
That is, of course, the title of 
I guess we don't have to worry about that baloney. I was hoping a good one would hit up here, so I could have an excuse for a day or two off work to catch up on my chores. We know how to deal with bad weather.