William M. Briggs

Statistician to the Stars!

Page 148 of 546

Woman To Marry Fairground Ride. A New Sexual ‘Orientation’?

Weeeeeeeeeeeee!

Weeeeeeeeeeeee!

I want you to tell me exactly why Amy Wolfe, a 33-year-old “US church organist”, can’t marry her favorite roller coaster. You heard me. Roller coaster—an “80ft gondola ride.” Exactly, now.

No fair saying, “It’s illegal”. Same-sex “marriage” is illegal in many spots too, but lots of people are still for it. Why shouldn’t she be allowed to do as she pleases?

Wolfe sure looks happy in a picture of her and her intended, surnamed “1001 Nachts”. The Daily Telegraph reports:

“I love him as much as women love their husbands and know we’ll be together forever,” she said.

Miss Wolfe first fell for the ride when she was 13: “I was instantly attracted to him sexually and mentally.

“I wasn’t freaked out, as it just felt so natural, but I didn’t tell anyone about it because I knew it wasn’t ‘normal’ to have feelings for a fairground ride.”

Point one: she said, “I’m not hurting anyone and I can’t help it…It’s a part of who I am.” So Wolfe ‘oriented’ towards roller coasters. If you say no, why?

It’s not an argument to laugh or scoff and say, “That’s absurd!” Maybe it is absurd: your job is to tell us why. It’s also not an argument to say why you’re in favor (if you are) of same-sex “marriage.” I don’t care—not here, anyway—unless the reason you’re in favor of SSM is the same as why Wolfe should be bound by matrimony to her ride.

No good using the word “obvious” in your proof. It’s obvious to me, for example, that SSM shouldn’t happen and that Wolfe needs a good psychiatrist; perhaps it’s obvious to you that SSM is A-okay and Wolfe is free to do what she wants. We have to go deeper than obvious.

Point two: though she didn’t use the word, in effect she said she’s “oriented” towards playground rides. Very well. Perhaps this “orientation” is biological; I mean, caused (in some way, we know not how) by her genes, raging hormones, or perhaps a swollen amygdala.

Coincidentally, I was reminded of a study by Bearrman and Bruckner: “Opposite-sex Twins and Adolescent Same-Sex Attraction (in American Journal of Sociology, 2002, pp 1179-1205).

Oddly, despite the popularity of the idea, the evidence for genetic and/or hormonal effects on same-sex orientation is inconclusive at best. The most publicized genetic findings, for example, the discovery of a marker for homosexuality in men (Hamer et al. 1993) has not been replicated, and studies purporting to establish a genetic or hormonal foundation to human sexual orientation to have serious methodological flaws.

The reason genetic markers are looked for is that it has been noticed that, sometimes, homosexual behavior runs in families. But then so does trout fishing. Meaning sometimes behavior is not genetically predetermined. Meaning that’s it’s possible, and even likely, that sexual behavior is at least sometimes chosen, a politically unwelcome idea. Anyway, with human behavior as complex as it is, it would be a wonder if there was just one explanation for our amorous proclivities.

Science News also reports “no major gene for homosexuality has been found despite numerous studies searching for a genetic connection”; instead some people are looking for epigenetic “shocks”, so to speak. But it’s all theoretical at this point, meaning the epigenetic idea “isn’t based on actual experiments,” quotes one scientist. (This is all necessary because evolutionary theory predicts genes for non-heterosexuality would quickly disappear because non-heterosexuals acting non-heterosexually don’t pass on their “selfish” genes.)

Even if the epigenetic shock theory were true, it wouldn’t explain people like Wolfe, those who are ‘oriented’ towards our four-legged friends, those oriented towards the infertile (children and the deceased; not much evolutionary advantage here), or folks with other non-standard desires.

The old-fashioned natural, scientific answer to today’s question is that marriage is between one man, one woman, mated for life and for the purpose of making and raising children. Used to be, up until about five, six years ago it was customary to acknowledge this, at least tacitly, especially the bit about kids.

People (even “researchers”) used to say that kids raised in homes with biological mom and dad did best. Evolutionary psychologists were even on board with this idea, saying (for example) adopted kids in man-woman families were under increased “risk” of death (step dads want to eliminate rival genes, you see). “Researchers” are now having to present data which “shows” that kids raised in any state whatsoever are equal to kids raised in scientific families. Given the loose requirements of statistical evidence, they’ll find it, too.


More On Flying

SFO to JFK. A Russian couple, both double-plus sized, the man at the aisle the woman the window. Me in the middle. I offered many times to let them sit together. No interest. They weren’t displeased with each other, judging by the matériel passed between them (and over me). They just didn’t want to move seats. They were both nice people.

The guy grabbed a magazine and flipped it open randomly. Full page line drawing of the kind of thing an OB-GYN would find familiar. Lots of precise anatomical detail, lovingly depicted. Because of my wide and diverse life experiences I knew just what I was seeing. I wondered if the people seated behind the man knew too.

Turns out the man was an OB-GYN. The article he was perusing, in a professional journal, was demonstrating all the different ways one might do an episiotomy. Where to place the fingers, best viewing angle, recommended knots, that sort of thing. I’m no expert, of course, but I thought the cross-patterned stitch was the most artistic.

This was Jet Blue and they unfortunately have televisions in the seat backs. It’s unfortunate because people seated at the windows find the televisions so fascinating that they almost always close the shades. Here we are, soaring through clear skies over what has to be the most beautiful mountain range in the world, blind to it. And wouldn’t it have been nice to see the lights of New York City (we came in at night)?

On the flight before last all but five windows were shuttered. The plane was illuminated to an artificial murk. Depressing.


Manhattan Methane Mystery: Or, A Curious Way To Argue For Green Energy

Today’s guest post is in the form of an extended email by Gerald E. Quindry, Ph.D., P.E. who noticed something peculiar about some official findings on methane measurements.

Dr Briggs,

In many of your posts, you have commented on the use, and abuse, of statistics in publications. Here is an example on which you may wish to comment. The documents I discuss below describe an investigation into the quantity of methane released from natural gas pipelines on the island of Manhattan. Both the preliminary and extended reports can be accessed from the Internet at: PDF link.

I came across these reports while searching for better, inexpensive method to monitor methane gas concentrations in air. I am an environmental engineer, and I have designed methane mitigation and monitoring systems for buildings constructed in areas where methane gas intrusion is a potential problem in building design. It may surprise you to learn that construction in a considerable portion of my home area of Southern California faces this issue. If you’ve ever been a tourist in Los Angeles, and visited the La Brea Tar Pits, the gas bubbles you see in the pits are…methane!

What first set off my “BS meter” was the following, from Page 20 of the “Extended” report:

These data were as follows:
Methane Concentrations in Ground-Level Air
Upwind 1.92 ppm ±0.003 ppm (99.9999% Confidence Interval)
Downwind 2.165 ppm ±0.021 ppm (99.9999% Confidence Interval)

I can’t recall ever before seeing chemical data presented with a “six nines” confidence interval; certainly never from data containing the kind of spatial and temporal variability that would be present in these data. I leave it to you, the “Statistician to the Stars” to explain how the numbers can be misinterpreted.

My real heartburn with the studies was the subsequent use of these data. These concentration values were used to calculate the change in methane levels in the air as it moved across Manhattan. Subsequently, that change was used to estimate the amount of methane released from the natural gas distribution piping underlying the City. (Natural gas is 85-95 percent methane.)

But a number can be both very precise, but very inaccurate, at the same time?

There are many potential sources of error in the analysis performed by the study. For example, there are many other sources of methane in the city, and no accounting of these other sources was made. Automobile exhaust contains methane from incomplete combustion of fuel. Sewers emit methane from the anaerobic bacteria that flourish there. Landfills and trash piles emit methane. Humans and animals emit methane. I also am doubtful that the analytical method used in the study was specific only to methane.

Many other volatile chemicals are released into the atmosphere, at restaurants, gas stations, dry cleaners, and the like. Paint contains volatile organic chemicals that are released while the paint dries. It is unclear that the data collected during the study would not be contaminated by passing near a release point for one of these air contaminants. Finally, (and this gets even deeper into the report methodology) it is my opinion that their treatment of boundary conditions and vertical mixing introduces huge potential errors in estimating the quantity of methane released to the atmosphere.

In summary, driving around the City, taking thousands of measurements of gas concentrations at the surface of the congested city streets, and then doing the calculations presented in the paper seems to be a poor choice in an attempt to quantify methane leaks from buried pipes.

The question then arises, why do the study? In my opinion, it is simply a side-battle in the climate change propaganda war.

Natural gas production in the United States is rising dramatically, due to advancements in the technology for drilling and extraction. The resulting oversupply of gas has dramatically reduced the price. That, in turn, has made it much more difficult for alternative energy projects to be economically viable without large, continuing, and reliable government subsidies. That has generated the need to discredit natural gas from its status as an economic, clean, and reliable energy source.

To accomplish this, the reports are publicized in a press release, “Natural Gas Emissions Measured in Manhattan Showing No Advantage to Natural Gas: Two Reports” (PDF) which is then picked up by the press and discussed on activist web sites, such as “New Study Exposes How Natural Gas Isn’t the Clean Fossil Fuel It’s Hyped up to Be” and “No smell of gas – but is that really OK?

In my opinion, this shouting from the extremes, practiced by both sides in the debate, is no way to develop the sound energy and environmental policy that we desperately need.

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Back to Briggs


Skipping the bizarre frequentist interpretation of confidence intervals and instead thinking like Bayesians, the “Upwind 1.92 ppm ±0.003 ppm (99.9999% Confidence Interval)” means that there is only a one in a million chance of seeing an upwind methane value outside the bounds 1.897 to 1.923 ppm for air coming into Manhattan. That’s strange because on p. 4 of the original report “Open country” values of 1.787 and 2.484 ppm were found.

They needed that narrow interval for their theory, though, which shows how much methane was supposedly added to air as it passed over Manhattan. If the interval on the incoming air was large, as it apparently should be, they could not claim leaky pipes added “8.6 billion cubic feet per year” (with no plus or minus) of methane.

Strangely, the confidence they claim on p. 4 is even higher: “highly reliable, 99.9999% confidence intervals ± <1% (0.021 ppm).” That’s sure some kind of confidence, boy.

And yes, a number can be both very precise, but very inaccurate, at the same time. You could have a gauge which prints readouts to arbitrary precision but which isn’t calibrated (the gauge reads “6.48572” but the actual value is “42”).

But skip all that. The most important part of Quindry’s criticisms are the other sources of over-confidence which the report does not address (such as the car exhaust, etc.).

Scientists Suddenly Discover Men Don’t Understand Women

Dr Brown demonstrates a portable fMRI device.

Dr Brown demonstrates a portable fMRI device.


Men are traditionally thought to have more problems in understanding women compared to understanding other men, though evidence supporting this assumption remains sparse.

So opens the peer-reviewed paper “Why Don’t Men Understand Women? Altered Neural Networks for Reading the Language of Male and Female Eyes” in PLOS One by Boris Schiffer and others.

Schiffer’s proposition is false, and glaringly so. There is abundant, indeed overwhelming evidence that men can’t figure women out but that those strange creatures largely have us brutes pegged. But then this paper was peer-reviewed and peer-reviewed papers only contain propositions which are ardently believed to be true, so what’s going on?

All is well if we understand that Schiffer’s use of “sparse” does not take its plain-English meaning of “thin or lacking”. Instead it means, “unpublished” as in “evidence supporting this obviously true statement remains unpublished.”

We must then forgive Schiffer and his co-authors because scientists are so desperate to publish that they will write about anything, even the obvious as if it weren’t.

So how did Schiffer and pals “discover” that men think differently than women? Maybe hooked them up to a brain-scanning machine and looked for which little gray cells glowed? And then examined the glowing regions for wee p-values which would pass peer review? Well, that’s it.

They grabbed 22 men off the street, asked them a bunch of questions—they said “administered” “instruments”1, but that’s how scientists talk—and then wired them to a machine with a lot of dials and knobs. They showed the men 36 pairs of eyes and then made them “decide which of the two presented words (e.g., distrustful or terrified) best described the emotional/mental state of the person whose eyes were presented.”

The guys also had to guess if the pictures were boy-eyes or girl-eyes (the “sex discrimination task”). What made it science was that, at the start of each round of pictures, they showed the words “‘Emotion’ or ‘Gender'” for precisely “seven seconds” (and not eight seconds). Time to answer was measured.

During the eye-watching, the fMRI machine took pictures of the fellows’ brains. The machines statistically manipulated the hell out of these images (“Bilinear interpolation”, “normalization”, “smoothed with an isotropic Gaussian kernel”, “boxcar function convolved with the hemodynamic response function”, “High-pass filtering with a cutoff frequency of 120 sec”). This alone gave employment to over a dozen people of your author’s bent.

Anyway, this manipulation obviously (it was prayed) had zero influence on the results. At least, any uncertainty in the manipulation was ignored, as is standard practice. Why rock the boat?

Then the real statistical models happened (“repeated measures analysis of variance”, “General Linear Model”, “ANOVAs”, p-values). The central finding is that “men exhibited significantly greater problems recognizing emotion than gender”.

Sorry, make that they had greater problems recognizing words related to emotion. They were able to pick off which eyes were female slightly better. Who could have guessed?

I know what’s on your mind. What of the amygdala? How can any proper paper on neurology fail to mention this most tiny feature of the brain which is said to cause just about everything we say or do? Breath easy: the amygdala is there. Indeed, “right amygdala activation modulated recognition accuracy.” So there.

And not only that, “The finding of heightened right amygdala responses during recognition of male compared to female stimuli might indicate a highly automated and stimulus-driven effect that occurred regardless of different conditions or instructions.” Or it might indicate men like looking at women more than they like looking at men and more than they like figuring which word pair maps to which eyes? Nah.

Besides a few other things, Schiffer also reported that men can tell which male eyes are angry better than they can tell which female eyes are angry (these may have been confused with “cute”). This may be because males spend more of their lives, particularly their formative years, with other males. But that’s the easy way out. A better explanation invokes evolutionary theory. IDing angry eyes

may have been a factor contributing to survival in ancient times. As men were more involved in hunting and territory fights, it would have been important for them to be able to predict and foresee the intentions and actions of their male rivals.


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1An “instrument” is a questionnaire or survey that somebody else used before you.

Thanks to Al and Ann Perrella for alerting us to this subject.

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