Hypotheses, Facts, and the Nature of Science
by Douglas Futuyma
ow,
for example, can you be sure that DNA is the genetic material? What if the
scientists who "proved" it made a mistake? Has anything really been proved
absolutely true? Is science merely one way—the dominant Western way—of
perceiving the world, no more or less valid than other perceptions of reality? Is
evolution a fact
or a theory? Or is it just an opinion I'm entitled to hold, just as creationists
are entitled to their opposite opinion?
Consider a hypothetical example. You are assigned to determine
why sheep are dying of an unknown disease. You take tissue samples from 50 healthy
and 50 sick sheep, and discover a certain protozoan in the liver of 20 of the sick
animals, but only 10 of the healthy ones. Is this difference enough to reject the
NULL
HYPOTHESIS: that the two groups of sheep do not
really differ in the incidence of protozoans? To answer this question, you do a
statistical test to see whether the difference between these numbers is too great
to have arisen merely by chance. You calculate the chi-square
(c2) statistic (it is 4.76),
look it up in a statistical table of chi-square values, and find that "0.025 <
p < 0.05." What does this expression, which you will find the like of in
almost all analyses of scientific data, mean? It means that (assuming you had a
random sample of sick sheep and healthy sheep) the probability is less than 0.05,
but more than 0.025, that the difference you found could have been due to chance
alone and that there is no real difference in protozoan infection rates of sick
and healthy sheep, at large.
Every experiment or observation in science is based on samples
from the larger universe of possible observations (all sheep, in this case), and in
every case, there is some chance that the data misrepresent the reality of this
larger universe. That is, it is always possible to mistakenly reject the null
hypothesis—the hypothesis that there is no difference between groups of sheep,
that there is no effect of an experimental manipulation, or that there is no
correlation between certain variables. In some cases, happily, the probability of
rejecting a true null hypothesis, and of accepting as true a false alternative
hypothesis, may be 0.00001 or less—in which case you would feel confident that
you can reject the null hypothesis, hut not absolutely certain.
So the study of 100 sheep supports the hypothesis that
sick sheep are more likely to have protozoans—but only weakly. You
suspect that the protozoans might be the cause of death, but you are worried by the
imperfect correlation. So you expand your sample to 1000 sheep, take liver biopsies
and examine them more carefully for protozoans (revealing cases that you might have
missed in your first study in which the protozoans are present, but at low density),
and record which sheep die within the following year. To your great satisfaction,
only 5 percent of the sheep in which you did not find protozoans die; 95 percent of
the infected sheep die, and when all the survivors are slaughtered at the end of the
year, you find that the apparently healthy sheep still show no sign of infection.
You triumphantly report to your advisor that the protozoan is the cause of the
disease. Right?
Wrong, says she. You haven't eliminated other hypotheses. Maybe
the disease is caused by a virus that incidentally also lowers the animals'
resistance to a relatively harmless protozoan. Maybe some sheep have a gene that
shortens their life and also lowers their resistance to infection. What you must do,
she says, is an experiment: inject some sheep, at random, with the protozoan and
others with a liquid that is the same except that it lacks the organism. You do so,
and after several failed experiments—it turns out that the infection doesn't
take unless the sheep consume the protozoan orally—you are delighted to report
that 90 of the 100 experimentally infected sheep died within 3 months, and 95 of the
100 "control" sheep lived through the 1-year duration of the experiment. The
chi-square test shows that p < 0.0001: there is an exceedingly low probability
that your results are due to chance.
At this point, you may have considerable confidence that the
protozoan causes disease and death. But you still haven't absolutely proved
it. Is it possible that you isolated and fed to the sheep not only protozoans, but
an unseen virus? Are you sure you infected sheep at random, or might you subconsciously
have chosen weaker-looking animals to infect? What do you suppose explains the 15
animals that didn't fit the hypothesis? And even if p < 0.0001, there's
still a chance, isn't there, that you had a bad "luck of the draw"? We need not
belabor the example longer, but it provides several lessons.
First, data in themselves tell us nothing: they have to be
interpreted in the light of theory and prior knowledge. In this example, we
need (among other things) probability theory (which underlies statistics such as the
chi-square test), the theory of experimental design, and the knowledge that viruses
exist and might confound our conclusions. The history of science is full of examples
of conclusions that had to be modified or rejected in the light of new theory and
information. Until the late 1950s, for instance, almost all geologists believed in
the fixed position of the continents; now all believe in plate tectonics and
continental drift, and many geological phenomena have had to be reinterpreted in
this light. Second, our hypothetical research experience shows us that arriving at a
confident conclusion takes a lot of work. It is easy to overlook that
every sentence in a textbook purporting to state a fact is based on research that
required immense effort, usually at least a few years of at least one person's
lifetime. For this reason, scientists usually defend their conclusions with
considerable vigor—a point to which we will soon return. Third, and most
important, research, no matter how carefully and painstakingly conceived and
executed, approaches proof, but never fully
attains it. There is always some chance, although it may seem almost
nonexistent, that the hypothesis you have come to accept will someday be modified
or rejected in the light of utterly new theories or data that we cannot now imagine.
Consequently, almost every scientific paper couches its conclusions in terms that
leave some room for doubt. In a paper on Drosophila genetics, that happened
just now to be within reach, I read the conclusion: the experiment "suggests that
different mechanisms mediate the two components of sperm displacement" (Clark et
al. 1995). The data are, in fact, exquisite, the experiment carefully designed,
the statistical analyses exemplary—but the authors do not claim to have
proved their point. Scientists often have immense confidence in their
conclusions, but not certainty. Accepting uncertainty as a fact of life is
essential to a good scientist's world view.
Any statement in science, then, should be understood as a
HYPOTHESIS—a statement of what might be true. Some hypotheses
are poorly supported. Others, such as the hypothesis that the earth revolves
around the sun, or that DNA is the genetic material, are so well supported that
we consider them to be facts. It is a mistake to think of a fact as
something that we absolutely know, with complete certainty, to be true, for we do
not know this of anything. (According to some philosophers, we cannot even be
certain that anything exists, including ourselves; how could we prove that the
world is not a self-consistent dream in the mind of God?) Rather, a fact is a
hypothesis that is so firmly supported by evidence that we assume it is true,
and act as if it were true.
Why should we share scientists' confidence in the statements
they propound as well-supported hypotheses or as facts? Because of the social
dynamics of science. A single scientist may well be mistaken (and, very rarely,
a scientist may deliberately falsify data). But if the issue is important,
if the progress of the field depends on it (as, for example, all of molecular
biology depends on the structure and function of DNA), then other scientists will
skeptically question the report. Some may deliberately try to replicate the
experiment; others will pursue research based on the assumption that the
hypothesis is true, and will find discrepancies if in fact it is false. In other
words, researchers in the field will test for error, because their own work and
their own careers are at stake. Moreover, scientists are motivated not only by
intellectual curiosity, but also by a desire for recognition or fame (although
they seldom can hope for fortune), and disproving a widely accepted hypothesis is
a ticket to professional recognition. Anyone who could show that heredity is
notbased on DNA, or that AIDS is not caused by the human immunodeficiency
virus, would be a scientific celebrity. Of course, those who originally propounded
the hypothesis have a lot at stake—a great investment of effort, and even
their reputations—so they typically defend their view passionately, even
sometimes in the face of damning evidence. The result of this process is that
every scientific discipline is full of controversies and intellectual battles
between proponents of opposing hypotheses. There is competition—a kind of
natural selection—among ideas, with the outcome decided by more evidence and
ever-more rigorous analysis, until even the most intransigent skeptics are won over
to a consensus view (or until they die off).
Evolution as Fact and Theory
Is evolution a fact, a theory, or a hypothesis? In science,
words are often used with precise meanings and connotations that differ from those
in everyday life. This is an exceedingly important point, and we will encounter
many examples in this book (e.g., fitness, random, correlation). Among such words
are hypothesis and theory. People often speak of a "mere" hypothesis (as in "it is
merely a hypothesis that smoking causes cancer") as if it were an opirtion
unsupported by evidence. In science, however, a hypothesis is an informed statement
of what might be true. It may be poorly supported, especially at first, but as we
have seen, it can gain support to the point at which it is effectively a fact. For
Copernicus, the revolution of the earth around the sun was a hypothesis with modest
support; for us, it is a hypothesis with strong support.
Likewise, a theory in science is not an unsupported speculation.
Rather, it is a mature, coherent body of interconnected statements, based on
reasoning and evidence, that explains a variety of
observations. Or, to quote the Oxford English Dictionary, a
theory is "a scheme or system of ideas and statements held as an explanation or
account of a group of facts or phenomena; a hypothesis that has been confirmed or
established by observation or experiment, and is propounded or accepted as accounting
for the known facts; a statement of what are known to be the general laws, principles,
or causes of something known or observed." Thus atomic theory, quantum theory, and
the theory of plate tectonics are not mere speculations or opinions, nor are they
even well-supported hypotheses (such as the hypothesis that smoking causes cancer).
Each is an elaborate scheme of interconnected ideas, strongly supported by evidence,
that accounts for a great variety of phenomena.
Because a theory
is a complex of statements, it usually does not stand or fall on the basis of a
single critical
test (as simple hypotheses often do). Rather, theories evolve as they are
confronted with new phenomena or observations; parts of the theory are discarded,
modified, added. The theory of heredity, for instance, consisted at first of
Mendel's laws of particulate inheritance, dominance,
and independent segregation of the "factors" (genes) that affect different
characteristics. Exceptions to dominance and independent segregation were soon found,
but the core principle of particulate inheritance remained. Building on and adding
to this core throughout the twentieth century, geneticists have developed a theory of
heredity far more complex and detailed than Mendel could have conceived. Parts of the
theory are exceedingly well established, other parts are still tentative, and we may
expect many additions and changes as the mechanisms of heredity and development are
plumbed further.
In light of the preceding discussion, evolution is a
scientific fact. But it is explained by
evolutionary theory. In The Origin of Species, Darwin propounded two large
hypotheses. One was descent, with modification, from common ancestors, or, for
simplicity, the hypothesis of descent with modification. I will also refer to this
as the "historical reality of evolution." The other large hypothesis was Darwin's
proposed cause for descent with modification: that
natural selection sorts among
hereditary variations.
Darwin provided abundant evidence for the historical reality
of evolution—for descent, with modification, from common ancestors. Even in
1859, this idea had considerable support. Within about 15 years, all biological
scientists except for a few diehards had accepted this hypothesis. Since then,
hundreds of thousands of observations, from paleontology, biogeography, comparative
anatomy, embryology, genetics, biochemistry, and molecular biology, have confirmed
it. Like the heliocentric hypothesis of Copernicus, the hypothesis of descent with
modification from common ancestors has long held the status of a scientific fact.
No biologist today would think of publishing a paper on "new evidence for
evolution," any more than a chemist would try to publish a demonstration that water
is composed of hydrogen and oxygen. It simply hasn't been an issue in scientific
circles for more than a century. Darwin hypothesized that the cause of evolution is
natural selection acting on hereditary variation. His argument was based on logic
and on interpretation of many kinds of circumstantial evidence, but he had no
direct evidence. More than 70 years would pass before an understanding of heredity
and the evidence for natural selection would fully vindicate his hypothesis.
Moreover, we now know that there are more causes of evolution than Darwin realized,
and that natural selection and hereditary variation themselves are more complex
than he imagined. Much of this book will be concerned with the complex body of
ideas—about mutation, recombination, gene flow, isolation,
random genetic
drift, the many forms of natural selection, and other factors—that
together constitute our current understanding of the causes of evolution.
This complex of interrelated ideas about the causes of
evolution is the theory of evolution, or "evolutionary theory." It is not a "mere
speculation," for all the ideas are supported by evidence. It is not a
hypothesis, but a body of hypotheses, most of which are well
supported. It is a theory in the sense defined in the preceding section. Like
all theories in science, it is incomplete, for we do not yet know the causes of
all of evolution, and some details may turn out to be wrong. But the main tenets
of evolutionary theory are so well supported that most biologists accept them
with confidence.
[ Douglas Futuyma,
Evolutionary
Biology, 3rd ed., Sinauer Associates, 1998, pp. 9-12. ]
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