Solving Problems in Biology

First, consider the question: "What is Science?"

A famous naturalist once said, "Without a hypothesis, a geologist might as well go into a gravel pit and count the stones."

A hypothesis is a "tentative proposition which is subject to verification through subsequent investigation....In many cases hypothese are hunches that the researcher has about the existence of relationships between variables." (Verma and Beard, 1981)

The hypothesis is the cornerstone of science, and hypotheses can be constructed and used in different ways.

In studies of complex, multi-factor systems (e.g., ecology and evolution), a hypothetico-deductive approach is often taken. On other areas, such as cellular and molecular biology, developmental biology, and other areas, hypotheses may be reached inductively, and a set of competing hypotheses potentially able to explain a given observed phenomenon may be tested and systematically eliminated until only the most likely explanations remain. To better understand each method, we should first review the differences between inductive and deductive reasoning.

Inductive vs. Deductive Reasoning

Scientists use both inductive and deductive reasoning to address biological problems.

Inductive Reasoning is sometimes called the "from the bottom up" approach. When we use inductive reasoning, our specific observations and measurements may begin to show us a general pattern. This might allow us to formulate a tentative hypothesis that can be further explored, and we might finally end up making some general conclusions.

In this case, one might construct an argument such as:

  • Items X, Y, and Z all have shown to have characteristic W.
  • Therefore, all items in the same class as X, Y and Z probably also have W.

    For example:

  • This bee stung me. It is a hymenopteran.
  • This wasp stung me. It is a hymenopteran.
  • This fire ant stung me. It is a hymenopteran.
  • I'm starting to see a pattern here. All hymenopterans have stingers.

    One potential pitfall here is the "inductive leap": When you make the jump from many specific observations to a general observation, your generalization might not be correct every time.

  • For example, many hymenopterans (stingless bees and ants, male honeybees, etc.) do not have stingers. (You might not discover this unless you test every single hymenopteran species for stinging capability.)

    Although generalizations are certainly useful, the wise investigator is aware that there may be exceptions to a general rule, and even to the possibility that the "general rule" might eventually be found to be wrong more often than not.

    Deductive Reasoning is sometimes called the "from the top down" approach. In this case, we start with a general idea and work down to the more specific.

    Deductive reasoning is used to test existing theories and hypotheses (general ideas) by collecting experimental observations (specific examples) that put those ideas to the test. One of the most useful ways to use this method is to construct a syllogism, a specific type of argument that has three simple steps:

  • Every X has the characteristic Y.
  • This thing in my hand is X.
  • Therefore, this thing has the characteristic Y.

    For example:

  • All wasps have stingers. (General idea that you inductively reached before.)
  • This thing in my hand is a wasp.
  • Therefore, this thing can probably sting me! (specific conclusion)
  • The experiment necessary to test this hypothesis might be painful.

    The results of your study may suggest further experiments. (What types of hymenopterans don't have stingers? Which is the primitive condition: stinger or no stinger? Why has stinglessness persisted?)

    Hypothesis, Theory, and Law.

    The Hypothesis

    The Theory

    The Law

    Science as Falsification

    German philosopher Karl Popper wrote in his famous essay, Science as Falsification, that it is vulnerability to falsification--not repeated verification--that is the hallmark of truly powerful hypothesis.

  • Scientific experiments are designed to rule out hypotheses that are clearly wrong.
  • This is done by what amounts to a "process of elmination" This process of exclusion is known as falsification.

    Ridiculously simple example:

    Until you do that one trial that nets a fish, the "no fish" hypothesis must be provisionally accepted, because your observable evidence does not suggest otherwise. But the scientist always must be open to the possibility that an unrefuted hypothesis may, at some point, be proven wrong.

    In the example above, it's easy to see that dipping a net into the ocean isn't a very high-tech way to address this problem. But with more advanced technology such as

    You might well be able to refute the "no fish" hypothesis. Science marches on as technology improves.

    If you're into metaphors, you might compare hypotheses constructed to Popperian standards to be like a castle or fortress...

    It may look well built from the outside, and seem to be perfectly sound. You may be able to add more blocks and mortar (analogous to finding evidence that appears to support your hypothesis: each dip of the net "confirmed" that there are no fish in the Pacific Ocean, right?)

    but until you test the "castle" by actually attacking it... don't really know how strong it is. If it wasn't well constructed, it may end up looking something like this:

    Statistical Hypotheses

    When an observation involves a relationship between two things, statistical tests are used to determine whether the two phenomena are, indeed, related.

    For example, if you want to know whether a new drug actually helps people quit smoking, the exploratory phase will involve a statistical question:

    "Will smokers taking SmokeAwaytm have a higher rate of giving up smoking than smokers given an indistinguishable placebo?"

    In this method, two muturally exclusive hypotheses are compared

    Strong Inference: Competing Hypotheses

    In 1964, John R. Platt coined the phrase "Strong Inference" to describe a method of inductive inference commonly used in certain scientific fields. The method is straightforward, powerful, and has been employed in some of the earliest and most elegant experiments in biology.

    Platt wrote:

    (Find the full text of this paper HERE.)

    The Differential Diagnosis scene in every episode of "House" is a bit like a cartoony, quick-n-dirty example of strong inference.

    The Scientific Method: Redux

    And so scientific study proceeds in a way that is very different from progress in other fields:

    The scientific method, requirement of physical evidence, falsification and, especially, WILLINGNESS TO MODIFY OR EVEN REJECT LONG-HELD IDEAS THAT TURN OUT TO BE WRONG are hallmarks of science, and are what sets them apart from religious faith. The two philosophies are entirely different, and should not be taught in the same context. References
    Platt, J. R., 1964, Strong inference. Science 146: 347-353.