Consider Classic Experiments

As part of the class I teach, the students get grades and complete some assignments on WebCT. One of them complained to me the other day about not being able to do something on the system and how much they loath it. I’m inclined to agree.

When I went to college, I didn’t actually want internet. I didn’t want to sit for hours at a time in front of the monitor surfing pointlessly, playing LAN games, or getting into trouble. Since I also know about Echelon, I also balked at the prospect of being tracked by the government whenever I opened a site, even if I ended up their accidentally. However, before too long, in one lab course I took in Biochemistry, we were required to, like my students are, complete assignments on WebCT.

If not for that, I probably would never have started a blog or wasted as much time as I have playing MMORPGs or in IM conversations. When it’s up to me, I prefer now to sit in my chair and read or play my guitar, now that it’s fixed. I find those things far more fulfilling, probably since I control them. You control very little on the internet.

Besides, old technology has its advantages. So many thieves have switched to online for easy money, that it’s almost become safe to send checks in the mail. Plus, they never steal a password for websites if I transact business via the USPS. It’s a lot of work to steal money through the mail, and you have to be physically there in order to do it. People can steal money from your account from the comfort of their home in Estonia while sitting nude smoking crack if they like.

Scientific technology likewise has come along so far that you can get publications for simpler things. For demonstrating that a gene has incomplete dominance or only a single allele (which is something they spend one whole lecture on in genetics classes), you can get into a journal because nobody does that anymore. A researcher in the lab I worked got his MS doing Chlorophyll fluorescence as a marker of stress. Nobody uses it, but it’s indisputable and very very easy, if only you own the equipment. Don’t ignore classics like Southern Blotting for ELISA or Y2H assays. Besides being simple and cheap, it leaves tangible results, not just readouts of electrons on a screen.

Federally Funded Fishing Expeditions

As a biochemist by training, I grow increasingly tired at claims that scientific media “proves” environmental decay, a genetic basis for deviant behavior, evolution, or that medication causes disease states. What most people, including sadly many scientists, don’t realize is that much of science is no longer hypothesis-driven, leading to false presumptions and inconclusive conclusions from the data we collect. Rather, in order to maximize publications and fame, scientists sacrifice the quest to solve problems and embark on federally funded fishing expeditions in hopes of collecting mass amounts of data and finding something there from with which to wow the public. Nobody seems interested in following through on a project that has end user application, because those quests take a lifetime without promise of any return on the investment. Worse, nobody will fund those who maintain this ethical problem-solving strategy because society demands results.

Science doesn’t prove anything. Science disproves all other possibilities until only the truth presumably remains. In a hypothesis-driven endeavor, one collects data and tries to refute the hypothesis. Evidence either refutes the belief or proves insufficient to disprove the hypothesis. In this way, no matter how overwhelming the data, the truth is never really proved, we are merely unable to disprove it. This phenomenon is easily illustrated by physics, which is highly content-specific: all that we know about resistance, gravity and acceleration forces and “constants” applies only in the context of the earth. Although the principles remain the same, all the parameters change when we leave the planet, and some forces change depending on our latitude on this one.

Non-scientists refuse to accept this fundamental truth of science- that we cannot “prove” much by experimentation. Data at best provides evidence that A and B are related or that A and B may be causative agents of C. Alec Guinness had a good line in “The Empire Strikes Back”, when he said that much of what we hold to be true depends on our point of view. This is especially important to consider in light of rogue scientists who will obscure or fabricate data, ignore variables, or withhold information to prevent others from subverting their personal agendas. They cannot prove what they believe, so they fit the data to their preconceived notions.

Despite the deception and delusions, the truth is not offended. Some day, we may come to know it, and then those who sowed lies will be refuted and lose whatever glory they thought they had.

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Unaccounted Variables

One of the first lab exercises I taught this semester dealt with simple use of the metric scale, but I found the opportunity to teach a much more powerful lesson in that part of our lab experience. When scientists plan experiments, we hope we take into account all the things that need to be controlled so that only one variable remains- the thing we intend to test. Due to ignorance, willful or innocent, however, sometimes things surprise us for which we do not account.

I asked the students to record the values on the board so that we could analyze the variance of data from person to person. I found another phenomenon that was easy to account for but not necessarily apparent. In the jar of pennies to weigh, there were pennies of different coinage. In 1981, the US Mint stopped coining pennies in pure copper and started wrapping copper around a zinc filler, changing the weight. Another student, unable to read apparently, weighed a 1000ml beaker instead of a 500ml one. This resulted in some widely varied numbers.

By and large, the students obtained weights where the only value that varied was in the last significant figure. That is common in science- it's the figure we're not EXACTLY certain of. For the different pennies (1997 and 1978), there was a 25% difference in weight (2.23 v. 3.41g). If you didn't know about the change in mintage and assumed that a penny was a penny, you might factor in both weights and have skewed data. Or you might throw out the one aberrant design because it was skew, but then you'd have to say "using pennies minted in the 1990s" in your description of the objects weighed. As for the beakers, it was easier to throw out the one value because he knew what he'd done wrong and could easily explain why it was okay to throw it out.

Outliers if not properly identified cannot be removed. That doesn't seem to stop many of my colleagues from deleting, losing or omitting data that counters the conclusion at which they wish to arrive. I have actually been TOLD by PhDs to omit data for various reasons. I must thank Genevieve Pont-Kingdon at ARUP for NEVER having given me the impression that so doing was acceptable.


In my last post, I mentioned briefly variegations across a species. Our lab studied 18 different cultivars of the species Vitis vinifera (wine grape), which isn't all of the cultivars available. There are at least seven members of the Vitis genus, and there are many other members of the fruiting vine family. To assume that Vitis vinifera cabernet sauvignon's behavior explains that of Vitis riparious (Norton- a North American native vine) or that of Watermelon would be silly, yet that's exactly what scientists try to tell us sometimes.

When I made conclusions, I said things like this:

For Vitis vinifera cultivar gewuertztraminer under water deficit stress in greenhouse conditions, we observed a 10-fold reduction of resveratrol in the leaves and a 2-fold reduction in the berries. A total of three biological samples were tested on three separate occasions to arrive at this figure.

I did not try to say that water deficit stress will affect other wine grapes grown in Africa or Iceland in the same way or that resveratrol was affected the same way systemically. You must restrict your conclusions to the limits you define or else you start running into other variables. Even then, sometimes they show up when you least expect it, even in something as simple as a penny.