"To the intelligent man or woman, life appears infinitely mysterious. But the stupid have an answer for every question." --Edward Abbey

I. How is science actually done?

1. Gathering facts is important. . .
   1. . . . but which facts do you gather? How do you know what facts to look for?
   2. You can gather facts to try to work out a general "law of nature" -- this is called induction. But how do you know when you have enough facts? How do you know you've got the right ones?
   3. As one of the great scientists of the 1800s once wrote. . .

      About thirty years ago there was much talk that geologists ought only to observe and not theorize; and I well remember someone saying that at this rate a man might as well go into a gravel-pit and count the pebbles and describe the colours. How odd it is that anyone should not see that all observation must be for or against some view if it is to be of any service.

2. While induction, or inductive methods, are still useful in many ways, the most commonly used scientific method is the hypothetico-deductive method:
   1. A scientist observes something that isn't explained.
   2. She formulates a hypothesis -- statement about how some aspect of the world might work.
      1. Often it's best to come up with multiple working hypotheses.
      2. In other words, try to come up with several possible explanations for something, so you don't get too attached to any one.
   3. She then puts hypothesis or hypotheses through some sort of test. . .
      1. which might be a formal experiment (more on this later. . .)
      2. or less controlled observations.
   4. The hypothesis is either rejected, or provisionally accepted. . .
      1. . . . but it must always be subject to further testing.
      2. The test results will hopefully lead to more hypotheses
      3. As you'll see later, a hypothesis that can't be tested isn't science.
3. Theory: a hypothesis that has been repeatedly tested and confirmed, and that is generally applicable in a wide range of situations.
   1. A very common error is to assume that "theory" means "guess" or "speculation" or "assumption that some dweeb in a white coat pulled out of thin air."
   2. The "Law of Gravity", radioactivity, the existence of atoms, bacteria causing disease, etc. are "only theories". . .
   3. They have been so thoroughly tested, we can pretty much assume they're close to truth -- at least they seem to work adequately in the real world. . .
   4. . . . but every now and then, even a well-tested theory gets shaken up and must be revised! (Example: Albert Einstein revolutionized the way people thought of the "Law of Gravity.")
4. There is NO absolute "proof" in science.
   1. Any test of a hypothesis is limited in space and time.
   2. But any theory that's interesting should go beyond what has been tested so far.
   3. A good theory will be the source of predictions that themselves can be tested.
   4. We can, however, disprove hypotheses and theories.
   5. A statement that cannot be disproven is not a scientific one.
5. Science may not "get it right" the first time. In fact, it usually doesn't.
   1. Scientists are anything but infallible -- the scientific community has its share of fools, idiots, bigots, close-minded arrogant twits, and even the occasional frauds and crooks. (Trust me on this; I've met all of them.)
   2. Even good scientists make mistakes -- it happens all the time.
   3. But science itself is dynamic and self-correcting.
   4. Hypotheses that don't work eventually get torn down, or at least modified. Mistakes and frauds may last a while, but eventually they get questioned, exposed, and dropped.

1. Suppose you want to test a hypothesis. (Let's say that our hypothesis is: taking certain pills keeps you from catching the flu.)
   Many different factors, or variables could be influencing and affecting what you see.
   1. For example, whether someone gets the flu or not could be affected by:
      • the weather
      • other medical conditions (such as allergies)
      • the people you come in contact with
      • your overall state of health (nutrition, etc.)
      • . . . and so on. . .
   2. A well-designed experiment will isolate only one of these variables.
   3. That way, it can test the hypothesis that that specific variable (the experimental variable) has an effect on something observed.
2. A good experiment uses controls.
   1. A control is a part of an experiment in which the variable being tested (the experimental variable) is left alone.
   2. Thus you can compare the control with the experimental group, in which you fiddle with the variable that you want to isolate and test (and only that variable).
      1. In a clinical trial, which is the best-known kind of experiment to the general public, we would divide a group of test subjects into two groups. In this example, all would have the flu, or be at risk for catching one. . .
      2. One group would get, say, Doctor Waggoner's Miracle Cure; the other group would get nothing.
      3. If the people who got the Miracle Cure got over their illness faster than those who did not, we would have confirmed the hypothesis.
      4. Note that we would have to match the experimental and control groups as closely as possible (same ages, genders, races, etc.)
         1. Watch for the placebo effect! In drug trials, people have been found to feel better, and get better, if they think they're getting an effective medicine (even if what they're getting is useless).
         2. To avoid this, in a clinical trial, both experimental and control groups receive a treatment, but the control group gets something completely ineffective (say, a pill made of sugar, or an injection of mild saltwater solution). This ineffective treatment is a placebo.
         3. Drug tests are usually done double-blind: Neither the patient, nor the doctor who gives the treatment, knows who is getting the placebo and who is getting the real drug.
3. Not all fields of science use experiments!
   1. Sometimes experiments aren't possible or aren't practical (e.g. geology, astronomy, meteorology, global climate research).
   2. In other cases, experiments are possible but would be unethical to do (e.g. certain areas of medicine, such as certain kinds of human brain research).
   3. In these fields, careful observation is the norm. We can't eliminate all the variables, but we can note carefully what they are and how they might work.
   4. Model building is another possible appproach -- experiments can be done on a model of something (whether a physical model, a mathematical model, or, more frequently these days, a computer model).
   5. Reasoning like a scientist often involves jumping back and forth between formal experiments, observations, modeling, and hypothesizing.
4. But regardless of how you do science, what you do must be reproducible.
   1. Anyone should be able to follow what you've done and find the same thing you did
   2. The real point of using "scientific jargon" should be to describe precisely. (Though it may not seem that way. . .)
   3. This is what makes science a universal endeavor -- anyone, whether capitalist, Communist, left-wing, right-wing, male, female, atheist, born-again, WHATEVER -- should be able to check an experiment's results, or someone's observations or models, and either confirm them or call them into question.
5. Now suppose that people with the flu take your pills and then get better. This still doesn't mean that the pills are doing any good, since most of the time people recover from flu even if they take no medicine at all!
   1. The post hoc fallacy is the assumption that if X happens, and then Y happens, that X must have caused Y. (Or in Latin, post hoc ergo propter hoc, which means "after it, therefore because of it.")
   2. This is a logical error -- two things may happen together, but that's no proof at all that one of them (such as taking the pills) caused the other (such as recovering from the flu).
      1. A study published in 2006 showed that there is a correlation between obesity and religious preference: conservative Protestant groups, in particular the Baptists, have higher rates of obesity than other faith groups.
      2. I'm not making that up. Check out this newspaper article for more information.
      3. The point is: We can't make quick judgments about what is causing what. Maybe there is something about Baptist religious practice that encourages obesity. . . or maybe obese people are likelier to become Baptists. . . or, maybe, both obesity and religious choice relate to a common third factor. . . or maybe it's a coincidence. Without further studies, we can't tell.
   3. Good experiments allow you to test whether X caused Y, rather than just assuming it blindly.

III. An untestable statement is not scientific and has no place in science. (This doesn't mean that untestable statements are useless or meaningless or wrong -- just that you can't use the "toolkit" of science to work with them.) Examples include (but are not limited to):

1. Aesthetics ("Beethoven's Seventh Symphony is more beautiful than Brahms's Fourth Symphony.")
2. Imprecise statements ("Like, when the sun shines on plants, like, stuff happens and, like, so they're all, like, kind of growing. Like, y'know?")
   1. Science isn't the same as mathematics. . .
   2. . . . but many branches of science use mathematics as a language, because it forces you to be precise about what you mean. . .
   3. . . . and the same applies to scientific vocabulary. It's a pain in the neck to learn all the long words that scientists often use -- but the reason they're useful is because they have very precise meanings, and they let you state precise, testable hypotheses.
      1. This hypothesis sounds complex. . . but once you learn what the words mean -- once you learn the code -- it's very testable, because it means something very specific: "LSD is an agonist of the 5HT2A and 5HT2C serotonin receptors in the brain."
      2. On the other hand, "LSD, like, wow, man. . . like, you see stuff, and it's like, oh, wow. . ." is easy to understand -- but it's too vague to be tested, and so it's not scientific.
3. Subjective statements ("There are elves in my medicine chest that no one else can see.")
4. Moral statements ("Everyone should vote Republican." "You should be willing to sacrifice your life for others.")
   1. This is sometimes called the "is-ought" dichotomy. . .
   2. Science can explain why the world is the way it is, and predict what will happen if you do certain things. . . but there is no logical way for it to tell you what you should do.
   3. The naturalistic fallacy is the logical mistake of asserting that something that is is something that should be. (Your professor is extremely nearsighted, but that doesn't mean that he shouldn't wear glasses. Some people are very aggressive, but that doesn't mean that they should kill other people if they want to.)
5. Supernatural and religious ideas ("The universe was created by the god Odhinn, and his brothers Vili and Ve, from the dismembered body parts of the corpse of the giant Ymir.")
   1. Scientists work with what we think of as natural forces and phenomena -- matter, energy, space, time.
   2. The "supernatural", whether it exists or not, is probably impossible to test. (And if it was testable, would it still be supernatural?)
   3. This doesn't mean scientists themselves must be atheists or agnostics -- in fact, religious beliefs of many kinds are fairly widespread among scientists.
   4. And it definitely doesn't mean that scientists don't feel awe and amazement and wonder at the world -- most of them definitely do!
   5. But it means that, in their work, scientists generally don't (or shouldn't) blend science with religion -- at least, not as the two terms are usually understood in our culture.
      • Example discussed in class: the 1999 Kansas City clinical trial of the effectiveness of prayer in recovery from heart attacks. It found a clinical benefit to intercessory prayer. . .
      • . . . but the latest and largest clinical test of intercessory prayer, called Study of the Therapeutic Effects of Intercessory Prayer (STEP), showed no benefits -- coronary bypass surgery patients who were prayed for by outsiders didn't do any better than patients who weren't. (Here's a recent newspaper article on the subject, or check out the official press release.)
      • Serious problems arise when you try to define and measure prayer and its effects. . . as we discussed.