Scientific Methods
The scientific
method is the process by which scientists, collectively and over time, endeavor
to construct an accurate (that is, reliable, consistent and non-arbitrary)
representation of the world.
Recognizing
that personal and cultural beliefs influence both our perceptions and our
interpretations of natural phenomena, we aim through the use of standard
procedures and criteria to minimize those influences when developing a theory.
As a famous scientist once said, "Smart people (like smart lawyers) can come
up with very good explanations for mistaken points of view."
In summary, scientific method attempts to minimize the influence of bias or prejudice
in experiment when testing an hypothesis or a theory.
1. Observation
and description of a phenomenon or group of phenomena.
2. Formulation
of an hypothesis to explain the phenomena. In physics, the hypothesis often
takes the form of a causal mechanism or a mathematical relation.
3. Use of the
hypothesis to predict the existence of other phenomena, or to predict
quantitatively the results of new observations.
4. Performance
of experimental tests of the predictions by several independent experimenters
and properly performed experiments.
If the
experiments bear out the hypothesis it may come to be regarded as a theory or
law of nature (more on the concepts of hypothesis, model, theory and law
below).
If the experiments do not bear out the hypothesis, it must be rejected
or modified. What is key in the description of the scientific method just given
is the predictive power (the ability to get more out of the theory than you put
in; see Barrow, 1991) of the hypothesis or theory, as tested by experiment. It
is often said in science that theories can never be proved, only disproved.
There is always the possibility that a new observation or a new experiment will
conflict with a long-standing theory.
As just
stated, experimental tests may lead either to the confirmation of the
hypothesis, or to the ruling out of the hypothesis. The scientific method
requires that an hypothesis be ruled out or modified if its predictions are
clearly and repeatedly incompatible with experimental tests. Further, no matter
how elegant a theory is, its predictions must agree with experimental results
if we are to believe that it is a valid description of nature. In physics, as
in every experimental science, "experiment is supreme" and
experimental verification of hypothetical predictions is absolutely necessary.
Experiments may test the theory directly (for example, the observation of a new
particle) or may test for consequences derived from the theory using
mathematics and logic (the rate of a radioactive decay process requiring the
existence of the new particle). Note that the necessity of experiment also
implies that a theory must be testable. Theories which cannot be tested,
because, for instance, they have no observable ramifications (such as, a
particle whose characteristics make it unobservable), do not qualify as scientific
theories.
If the
predictions of a long-standing theory are found to be in disagreement with new
experimental results, the theory may be discarded as a description of reality,
but it may continue to be applicable within a limited range of measurable
parameters. For example, the laws of classical mechanics (Newton's Laws) are
valid only when the velocities of interest are much smaller than the speed of
light (that is, in algebraic form, when v/c << 1). Since this is the
domain of a large portion of human experience, the laws of classical mechanics
are widely, usefully and correctly applied in a large range of technological
and scientific problems. Yet in nature we observe a domain in which v/c is not
small. The motions of objects in this domain, as well as motion in the
"classical" domain, are accurately described through the equations of
Einstein's theory of relativity. We believe, due to experimental tests, that
relativistic theory provides a more general, and therefore more accurate, description
of the principles governing our universe, than the earlier
"classical" theory. Further, we find that the relativistic equations
reduce to the classical equations in the limit v/c << 1. Similarly,
classical physics is valid only at distances much larger than atomic scales (x
>> 10-8 m). A description which is valid at all length
scales is given by the equations of quantum mechanics.
We are all
familiar with theories which had to be discarded in the face of experimental
evidence. In the field of astronomy, the earth-centered description of the
planetary orbits was overthrown by the Copernican system, in which the sun was
placed at the center of a series of concentric, circular planetary orbits.
Later, this theory was modified, as measurements of the planets motions were
found to be compatible with elliptical, not circular, orbits, and still later
planetary motion was found to be derivable from Newton's laws.
Error in
experiments have several sources. First, there is error intrinsic to
instruments of measurement. Because this type of error has equal probability of
producing a measurement higher or lower numerically than the "true"
value, it is called random error. Second, there is non-random or systematic
error, due to factors which bias the result in one direction. No measurement,
and therefore no experiment, can be perfectly precise. At the same time, in
science we have standard ways of estimating and in some cases reducing errors.
Thus it is important to determine the accuracy of a particular measurement and,
when stating quantitative results, to quote the measurement error. A
measurement without a quoted error is meaningless. The comparison between
experiment and theory is made within the context of experimental errors.
Scientists ask, how many standard deviations are the results from the
theoretical prediction? Have all sources of systematic and random errors been
properly estimated? This is discussed in more detail in the appendix on Error
Analysis and in Statistics Lab 1.
As stated
earlier, the scientific method attempts to minimize the influence of the
scientist's bias on the outcome of an experiment. That is, when testing an
hypothesis or a theory, the scientist may have a preference for one outcome or
another, and it is important that this preference not bias the results or their
interpretation. The most fundamental error is to mistake the hypothesis for an
explanation of a phenomenon, without performing experimental tests. Sometimes
"common sense" and "logic" tempt us into believing that no
test is needed. There are numerous examples of this, dating from the Greek
philosophers to the present day.
Another common
mistake is to ignore or rule out data which do not support the hypothesis.
Ideally, the experimenter is open to the possibility that the hypothesis is
correct or incorrect. Sometimes, however, a scientist may have a strong belief
that the hypothesis is true (or false), or feels internal or external pressure
to get a specific result. In that case, there may be a psychological tendency
to find "something wrong", such as systematic effects, with data
which do not support the scientist's expectations, while data which do agree
with those expectations may not be checked as carefully. The lesson is that all
data must be handled in the same way.
Another common
mistake arises from the failure to estimate quantitatively systematic
errors (and all errors). There are many examples of discoveries which were
missed by experimenters whose data contained a new phenomenon, but who
explained it away as a systematic background. Conversely, there are many
examples of alleged "new discoveries" which later proved to be due to
systematic errors not accounted for by the "discoverers."
In a field
where there is active experimentation and open communication
among members of the scientific community, the biases of individuals or groups
may cancel out, because experimental tests are repeated by different scientists
who may have different biases. In addition, different types of experimental
setups have different sources of systematic errors. Over a period spanning a
variety of experimental tests (usually at least several years), a consensus
develops in the community as to which experimental results have stood the test
of time.
IV. Hypotheses, Models, Theories and Laws
In physics and
other science disciplines, the words "hypothesis," "model,"
"theory" and "law" have different connotations in relation
to the stage of acceptance or knowledge about a group of phenomena.
An hypothesis is
a limited statement regarding cause and effect in specific situations; it also
refers to our state of knowledge before experimental work has been performed
and perhaps even before new phenomena have been predicted. To take an example
from daily life, suppose you discover that your car will not start. You may
say, "My car does not start because the battery is low." This is your
first hypothesis. You may then check whether the lights were left on, or if the
engine makes a particular sound when you turn the ignition key. You might
actually check the voltage across the terminals of the battery. If you discover
that the battery is not low, you might attempt another hypothesis ("The
starter is broken"; "This is really not my car.")
The word model is
reserved for situations when it is known that the hypothesis has at least
limited validity. A often-cited example of this is the Bohr model of the atom,
in which, in an analogy to the solar system, the electrons are described has
moving in circular orbits around the nucleus. This is not an accurate depiction
of what an atom "looks like," but the model succeeds in
mathematically representing the energies (but not the correct angular momenta)
of the quantum states of the electron in the simplest case, the hydrogen atom.
Another example is Hook's Law (which should be called Hook's principle, or
Hook's model), which states that the force exerted by a mass attached to a
spring is proportional to the amount the spring is stretched. We know that this
principle is only valid for small amounts of stretching. The "law"
fails when the spring is stretched beyond its elastic limit (it can break).
This principle, however, leads to the prediction of simple harmonic motion,
and, as a model of the behavior of a spring, has been versatile
in an extremely broad range of applications.
A scientific
theory or law represents an hypothesis, or a group of related
hypotheses, which has been confirmed through repeated experimental tests.
Theories in physics are often formulated in terms of a few concepts and
equations, which are identified with "laws of nature," suggesting
their universal applicability. Accepted scientific theories and laws become
part of our understanding of the universe and the basis for exploring less
well-understood areas of knowledge. Theories are not easily discarded; new
discoveries are first assumed to fit into the existing theoretical framework.
It is only when, after repeated experimental tests, the new phenomenon cannot
be accommodated that scientists seriously question the theory and attempt to
modify it. The validity that we attach to scientific theories as representing
realities of the physical world is to be contrasted with the facile
invalidation implied by the expression, "It's only a theory." For
example, it is unlikely that a person will step off a tall building on the
assumption that they will not fall, because "Gravity is only a
theory."
Changes in
scientific thought and theories occur, of course, sometimes revolutionizing our
view of the world (Kuhn, 1962). Again, the key force for change is the
scientific method, and its emphasis on experiment.
While the
scientific method is necessary in developing scientific knowledge, it is also
useful in everyday problem-solving. What do you do when your telephone doesn't
work? Is the problem in the hand set, the cabling inside your house, the hookup
outside, or in the workings of the phone company? The process you might go
through to solve this problem could involve scientific thinking, and the
results might contradict your initial expectations.
Like any good
scientist, you may question the range of situations (outside of science) in
which the scientific method may be applied. From what has been stated above, we
determine that the scientific method works best in situations where one can
isolate the phenomenon of interest, by eliminating or accounting for extraneous
factors, and where one can repeatedly test the system under study after making
limited, controlled changes in it.
There are, of
course, circumstances when one cannot isolate the phenomena or when one cannot
repeat the measurement over and over again. In such cases the results may
depend in part on the history of a situation. This often occurs in social
interactions between people. For example, when a lawyer makes arguments in
front of a jury in court, she or he cannot try other approaches by repeating
the trial over and over again in front of the same jury. In a new trial, the
jury composition will be different. Even the same jury hearing a new set of
arguments cannot be expected to forget what they heard before.
The scientific
method is intricately associated with science, the process of human inquiry
that pervades the modern era on many levels. While the method appears simple
and logical in description, there is perhaps no more complex question than that
of knowing how we come to know things. In this introduction, we have emphasized
that the scientific method distinguishes science from other forms of
explanation because of its requirement of systematic experimentation. We have
also tried to point out some of the criteria and practices developed by
scientists to reduce the influence of individual or social bias on scientific
findings. Further investigations of the scientific method and other aspects of
scientific practice may be found in the references listed below.
1. Wilson, E.
Bright. An Introduction to Scientific Research (McGraw-Hill,
1952).
2. Kuhn,
Thomas. The Structure of Scientific Revolutions (Univ. of Chicago Press, 1962).
3. Barrow,
John. Theories of Everything (Oxford Univ. Press, 1991).
No comments