Methodology
[Scientific Method, see below]
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Methodology is defined as
1. "the analysis of the principles of methods, rules, and postulates employed by a
discipline",
2. "the systematic study of methods that are, can be, or have been applied within a
discipline" or
3. "a particular procedure or set of procedures" [1].
It should be noted that methodology is frequently used when method would be more
accurate. (This is a classic example of word inflation.) For example, "Since students were
not available to complete the survey about academic success, we changed our
methodology and gathered data from instructors instead". In this instance the
methodology (gathering data via surveys, and the assumption that this produces accurate
results) did not change, but the method (asking teachers instead of students) did.
Methodology includes the following concepts as they relate to a particular discipline or
field of inquiry:
1. a collection of theories, concepts or ideas;
2. comparative study of different approaches; and
3. critique of the individual methods
Methodology refers to more than a simple set of methods; rather it refers to the rationale
and the philosophical assumptions that underlie a particular study. This is why scholarly
literature often includes a section on the methodology of the researchers. This section
does more than outline the researchers’ methods (as in, “We conducted a survey of 50
people over a two-week period and subjected the results to statistical analysis”, etc.); it
might explain what the researchers’ ontological or epistemological views are.
Another key (though arguably imprecise) usage for methodology does not refer to
research or to the specific analysis techniques. This often refers to anything and
everything that can be encapsulated for a discipline or a series of processes, activities and
tasks. Examples of this are found in software development, project management and
business process fields. This use of the term is typified by the outline who, what, where,
when & why. In the documentation of the processes that make up the discipline, that is
being supported by "this" methodology, that is where we would find the "methods" or
processes. The processes themselves are only part of the methodology along with the
identification and usage of the standards, policies, rules, etc.
Contents
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1 Example
2 Set of methods
3 See also
4 References
5 Further reading
[edit] Example
The tone or style of this article or section may not be appropriate for
Wikipedia.
Specific concerns may be found on the talk page. See Wikipedia's guide to writing better
articles for suggestions.(December 2007)
Hence, in properly conceived methodologies, researchers typically acknowledge their
fundamental approaches to reality. For example: Do researchers believe in the paradigm of Positivism, which holds that truth is out
there waiting to be discovered? In this view, facts exist independently of any
theories or human observation. This perspective dominates Western philosophical
tradition which provides the foundation of Western science: reality is assumed to
be objective, that is, it exists outside our perception. In this paradigm, neither the
search for truth nor truth itself is problematic: Truth (with a capital "T") is definite
and ascertainable. The “men in white coats” conduct an empirical experiment in a
lab, and then announce to the rest of us what they, as “experts,” have discovered.
Or is truth constructed (see Constructivism and Constructivist epistemology)
within the minds of individuals and between people in a culture? In this view,
facts become "facts" and are a construct of theories and points of view. This
paradigm holds that both the nature of truth and the inquiry into that truth are
problematic because truth is built (or constructed) from the ongoing processes of
negotiation, reevaluation and refinement of and between individuals.
[edit] Set of methods
Most sciences have their own specific scientific methods, which are supported by
methodologies (i.e., rationale that support the method's validity).
The social sciences are methodologically diverse using qualitative, quantitative, and
mixed-methods approaches. Qualitative methods include the case study, phenomenology,
grounded theory, and ethnography, among others. Quantitative methods include
hypothesis testing, power analysis, metanalysis, observational studies, resampling,
randomized controlled trials, regression analysis, multilevel modeling, and highdimensional data analysis, among others.
[edit] See also
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Power of a method
Thought
[edit] References
1. ^ Merriam–Webster
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Creswell, J. (1998). Qualitative inquiry and research design: Choosing among
five traditions. Thousand Oaks, California: Sage Publications.
Creswell, J. (2003). Research Design: Qualitative, Quantitative, and Mixed
Methods Approaches. Thousand Oaks, California: Sage Publications.
Guba, E. and Lincoln, Y. (1989). Fourth Generation Evaluation. Newbury Park,
California: Sage Publications.
Patton, M.Q. (2002). Qualitative research & evaluation methods (3rd edition).
Thousand Oaks, California: Sage Publications.
Webster's New International Dictionary of the English Language, Second Edition,
Unabridged, W.A. Neilson, T.A. Knott, P.W. Carhart (eds.), G. & C. Merriam
Company, Springfield, MA, 1950.
[edit] Further reading
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Usage note on the word Methodology
Scientific method
From Wikipedia, the free encyclopedia
Jump to: navigation, search
Scientific method Portal
Scientific method is a body of techniques for investigating phenomena, acquiring new
knowledge, or correcting and integrating previous knowledge. It is based on gathering
observable, empirical and measurable evidence subject to specific principles of
reasoning.[1] A scientific method consists of the collection of data through observation
and experimentation, and the formulation and testing of hypotheses.[2]
Although procedures vary from one field of inquiry to another, identifiable features
distinguish scientific inquiry from other methodologies of knowledge. Scientific
researchers propose hypotheses as explanations of phenomena, and design experimental
studies to test these hypotheses. These steps must be repeatable in order to predict
dependably any future results. Theories that encompass wider domains of inquiry may
bind many hypotheses together in a coherent structure. This in turn may help form new
hypotheses or place groups of hypotheses into context.
Among other facets shared by the various fields of inquiry is the conviction that the
process must be objective to reduce a biased interpretation of the results. Another basic
expectation is to document, archive and share all data and methodology so it is available
for careful scrutiny by other scientists, thereby allowing other researchers the opportunity
to verify results by attempting to reproduce them. This practice, called full disclosure,
also allows statistical measures of the reliability of these data to be established.
Contents
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1 Introduction to scientific method
2 Truth and belief
3 Elements of scientific method
o 3.1 DNA example
o 3.2 Characterizations
 3.2.1 Uncertainty
 3.2.2 Definition
 3.2.3 DNA-characterizations
 3.2.4 Precession of Mercury
o 3.3 Hypothesis development
 3.3.1 DNA-hypotheses
o 3.4 Predictions from the hypothesis
 3.4.1 General relativity
o 3.5 Experiments
 3.5.1 DNA-experiments
4 Evaluation and iteration
o 4.1 Testing and improvement
 4.1.1 DNA-iterations
o 4.2 Confirmation
5 Models of scientific inquiry
o 5.1 Classical model
o 5.2 Pragmatic model
o 5.3 Computational approaches
6 Philosophy and sociology of science
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7 Communication, community, culture
o 7.1 Peer review evaluation
o 7.2 Documentation and replication
 7.2.1 Archiving
 7.2.2 Dearchiving
 7.2.3 Limitations
o 7.3 Dimensions of practice
8 History
9 Relationship with mathematics
10 Notes and references
11 Further reading
12 See also
o 12.1 Synopsis of related topics
o 12.2 Logic, mathematics, methodology
o 12.3 Problems and issues
o 12.4 History, philosophy, sociology
13 External links
[edit] Introduction to scientific method
Ibn al-Haytham, 965–1039, Basra
From Ibn al-Haytham (Alhacen, 965–1039, a pioneer of scientific method) to the present
day, the emphasis has been on seeking truth:
"Truth is sought for its own sake. And those who are engaged upon the
quest for anything for its own sake are not interested in other things.
Finding the truth is difficult, and the road to it is rough."[3]
"How does light travel through transparent bodies? Light travels through
transparent bodies in straight lines only. ... We have explained this
exhaustively in our Book of Optics. But let us now mention something to
prove this convincingly: the fact that light travels in straight lines is clearly
observed in the lights which enter into dark rooms through holes.... [T]he
entering light will be clearly observable in the dust which fills the air."[4]
Alhacen (1000): light travels in straight lines
The conjecture that "Light travels through transparent bodies in straight lines only", was
corroborated by Alhacen only after years of effort. His demonstration of the conjecture
was to place a straight stick or a taut thread next to the light beam,[5] to prove that light
travels in a straight line.
Scientific methodology has been practiced in some form for at least one thousand years.
There are difficulties in a formulaic statement of method, however. As William Whewell
(1794-1866) noted in his History of Inductive Science (1837) and in Philosophy of
Inductive Science (1840), "invention, sagacity, genius" are required at every step in
scientific method. It is not enough to base scientific method on experience alone[6];
multiple steps are needed in scientific method, ranging from our experience to our
imagination, back and forth.
In the twentieth century, a hypothetico-deductive model for scientific method was
formulated (for a more formal discussion, see below):
1. Use your experience - consider the problem and try to make sense of it. Look
for previous explanations; if this is a new problem to you, then do
2. Conjecture an explanation - when nothing else is yet known, try to state your
explanation, to someone else, or to your notebook.
3. Deduce a prediction from that explanation- if 2 were true, then state a
consequence of that explanation.
4. Test - look for the opposite of that consequence in order to disprove 2. It is a
logical error to seek 3 directly as proof of 2. This error is called affirming the
consequent.
This model underlies the scientific revolution. One thousand years ago, Alhacen
demonstrated the importance of steps 1 and 4. Galileo (1638) also showed the importance
of step 4 (also called Experiment) in Two New Sciences. One possible sequence in this
model would be 1, 2, 3, 4. If the outcome of 4 holds, and 3 is not yet disproven, you may
continue with 3, 4, 1, and so forth; but if the outcome of 4 shows 3 to be false, you will
have go back to 2 and try to invent a new 2, deduce a new 3, look for 4, and so forth.
Note that 2 can never be shown to be absolutely true by scientific method[7]; only that 2
can be shown to be absolutely false by scientific method. (This is what Einstein meant
when he said "No amount of experimentation can ever prove me right; a single
experiment can prove me wrong.")
In the twentieth century, Ludwik Fleck (1896-1961) and others found that we need to
consider our experiences more carefully, because our experience may be biased, and that
we need to be more exact when describing our experiences. These considerations are
discussed below.
Flying horse depiction: disproven; see below
[edit] Truth and belief
Main article: Truth
Belief can alter observations; those with a particular belief will often see things as
reinforcing their belief, even if they do not.[8] Needham's Science and Civilization in
China uses the 'flying horse' image as an example of observation: in it, a horse's legs are
depicted as splayed, when the stop-action picture by Eadweard Muybridge shows
otherwise. Note that at the moment that no hoof is touching the ground, the horse's legs
are gathered together and are not splayed.
Eadweard Muybridge's studies of a horse galloping
Earlier paintings depict the incorrect flying horse observation. This demonstrates Ludwik
Fleck's caution that people observe what they expect to observe, until shown otherwise;
our beliefs will affect our observations (and therefore our subsequent actions). The
purpose of the scientific method is to test a hypothesis, a belief about how things are, via
repeatable experimental observations which can contradict the hypothesis so as to fight
this observer bias.
[edit] Elements of scientific method
There are many ways of outlining the basic method shared by all fields of scientific
inquiry. The following examples are typical classifications of the most important
components of the method on which there is wide agreement in the scientific community
and among philosophers of science. There are, however, disagreements about some
aspects.
The following set of methodological elements and organization of procedures tends to be
more characteristic of natural sciences than social sciences. In the social sciences
mathematical and statistical methods of verification and hypotheses testing may be less
stringent. Nonetheless the cycle of hypothesis, verification and formulation of new
hypotheses will resemble the cycle described below.
The essential elements[9][10][11] of a scientific method[12] are iterations,[13]
recursions,[14] interleavings, and orderings of the following:
(observations,[15] definitions, and measurements of the
subject of inquiry)
 Characterizations
 Hypotheses[16][17]
(theoretical, hypothetical explanations of observations and
measurements of the subject)[18]
 Predictions
(reasoning including logical deduction[19] from the hypothesis or
theory)
 Experiments[20]
(tests of all of the above)
Each element of a scientific method is subject to peer review for possible mistakes. These
activities do not describe all that scientists do (see below) but apply mostly to
experimental sciences (e.g., physics, chemistry). The elements above are often taught in
the educational system.[21]
Scientific method is not a recipe: it requires intelligence, imagination, and creativity.[22] It
is also an ongoing cycle, constantly developing more useful, accurate and comprehensive
models and methods. For example, when Einstein developed the Special and General
Theories of Relativity, he did not in any way refute or discount Newton's Principia. On
the contrary, if the astronomically large, the vanishingly small, and the extremely fast are
reduced out from Einstein's theories — all phenomena that Newton could not have
observed — Newton's equations remain. Einstein's theories are expansions and
refinements of Newton's theories, and observations that increase our confidence in them
also increase our confidence in Newton's approximations to them.
A linearized, pragmatic scheme of the four points above is sometimes offered as a
guideline for proceeding:[23]
1. Define the question
2. Gather information and resources (observe)
3.
4.
5.
6.
Form hypothesis
Perform experiment and collect data
Analyze data
Interpret data and draw conclusions that serve as a starting point for new
hypothesis
7. Publish results
8. Retest (frequently done by other scientists)
The iterative cycle inherent in this step-by-step methodology goes from point 3 to 6 back
to 3 again.
While this schema outlines a typical hypothesis/testing method,[24] it should also be noted
that a number of philosophers, historians and sociologists of science (perhaps most
notably Paul Feyerabend) claim that such descriptions of scientific method have little
relation to the ways science is actually practiced.
The "operational" model combines the concepts of factory-style processing, operational
definition, and utility:
The essential elements of a scientific method are operations, observations, models,
and a utility function for evaluating models.[citation needed]
 Operation
- Some action done to the system being investigated
 Observation
- What happens when the operation is done to the system
 Model
- A fact, hypothesis, theory, or the phenomenon itself at a certain
moment
 Utility Function
- A measure of the usefulness of the model to explain, predict,
and control, and of the cost of use of it. One of the elements of any scientific
utility function is the refutability of the model. Another is its simplicity, on
the Principle of Parsimony also known as Occam's Razor.
The Keystones of Science project, sponsored by the journal Science, has selected a
number of scientific articles from that journal and annotated them, illustrating how
different parts of each article embody scientific method. Here is an annotated example of
this scientific method example titled Microbial Genes in the Human Genome: Lateral
Transfer or Gene Loss?.
[edit] DNA example
Each element of scientific method is illustrated below by an example from the
discovery of the structure of DNA:
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DNA-characterizations: in this case, although the significance of the gene
had been established, the mechanism was unclear to anyone, as of 1950.
DNA-hypotheses: Crick and Watson hypothesized that the gene had a
physical basis - it was helical.
DNA-predictions: from earlier work on tobacco mosaic virus, Watson was
aware of the significance of Crick's formulation of the transform of a
helix.[25] Thus he was primed for the significance of the X-shape in photo
51.
DNA-experiments: Watson sees photo 51.
The examples are continued in "Evaluations and iterations" with DNA-iterations.
[edit] Characterizations
Scientific method depends upon increasingly more sophisticated characterizations of
subjects of the investigation. (The subjects can also be called unsolved problems or the
unknowns). For example, Benjamin Franklin correctly characterized St. Elmo's fire as
electrical in nature, but it has taken a long series of experiments and theory to establish
this. While seeking the pertinent properties of the subjects, this careful thought may also
entail some definitions and observations; the observations often demand careful
measurements and/or counting.
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"I am not accustomed to saying anything with certainty after only one or two
observations."[26] --Andreas Vesalius (1546)
The systematic, careful collection of measurements or counts of relevant quantities is
often the critical difference between pseudo-sciences, such as alchemy, and a science,
such as chemistry or biology. Scientific measurements taken are usually tabulated,
graphed, or mapped, and statistical manipulations, such as correlation and regression,
performed on them. The measurements might be made in a controlled setting, such as a
laboratory, or made on more or less inaccessible or unmanipulatable objects such as stars
or human populations. The measurements often require specialized scientific instruments
such as thermometers, spectroscopes, or voltmeters, and the progress of a scientific field
is usually intimately tied to their invention and development.
[edit] Uncertainty
Measurements in scientific work are also usually accompanied by estimates of their
uncertainty. The uncertainty is often estimated by making repeated measurements of the
desired quantity. Uncertainties may also be calculated by consideration of the
uncertainties of the individual underlying quantities that are used. Counts of things, such
as the number of people in a nation at a particular time, may also have an uncertainty due
to limitations of the method used. Counts may only represent a sample of desired
quantities, with an uncertainty that depends upon the sampling method used and the
number of samples taken.
[edit] Definition
Measurements demand the use of operational definitions of relevant quantities. That is, a
scientific quantity is described or defined by how it is measured, as opposed to some
more vague, inexact or "idealized" definition. For example, electrical current, measured
in amperes, may be operationally defined in terms of the mass of silver deposited in a
certain time on an electrode in an electrochemical device that is described in some detail.
The operational definition of a thing often relies on comparisons with standards: the
operational definition of "mass" ultimately relies on the use of an artifact, such as a
certain kilogram of platinum-iridium kept in a laboratory in France.
The scientific definition of a term sometimes differs substantially from its natural
language usage. For example, mass and weight overlap in meaning in common discourse,
but have distinct meanings in mechanics. Scientific quantities are often characterized by
their units of measure which can later be described in terms of conventional physical
units when communicating the work.
New theories sometimes arise upon realizing that certain terms had not previously been
sufficiently clearly defined. For example, Albert Einstein's first paper on relativity begins
by defining simultaneity and the means for determining length. These ideas were skipped
over by Isaac Newton with, "I do not define time, space, place and motion, as being well
known to all." Einstein's paper then demonstrates that they (viz., absolute time and length
independent of motion) were approximations. Francis Crick cautions us that when
characterizing a subject, however, it can be premature to define something when it
remains ill-understood.[27] In Crick's study of consciousness, he actually found it easier to
study awareness in the visual system, rather than to study free will, for example. His
cautionary example was the gene; the gene was much more poorly understood before
Watson and Crick's pioneering discovery of the structure of DNA; it would have been
counterproductive to spend much time on the definition of the gene, before them.
[edit]
DNA-characterizations
The history of the discovery of the structure of DNA is a classic example of the
elements of scientific method: in 1950 it was known that genetic inheritance had a
mathematical description, starting with the studies of Gregor Mendel. But the
mechanism of the gene was unclear. Researchers in Bragg's laboratory at
Cambridge University made X-ray diffraction pictures of various molecules,
starting with crystals of salt, and proceeding to more complicated substances.
Using clues which were painstakingly assembled over the course of decades,
beginning with its chemical composition, it was determined that it should be
possible to characterize the physical structure of DNA, and the X-ray images
would be the vehicle. ..2. DNA-hypothesesdna is an atom
[edit] Precession of Mercury
Precession of the perihelion (exaggerated)
The characterization element can require extended and extensive study, even
centuries. It took thousands of years of measurements, from the Chaldean, Indian,
Persian, Greek, Arabic and European astronomers, to record the motion of planet
Earth. Newton was able to condense these measurements into consequences of his
laws of motion. But the perihelion of the planet Mercury's orbit exhibits a
precession which is not fully explained by Newton's laws of motion. The
observed difference for Mercury's precession, between Newtonian theory and
relativistic theory (approximately 43 arc-seconds per century), was one of the
things that occurred to Einstein as a possible early test of his theory of General
Relativity.
[edit] Hypothesis development
A hypothesis is a suggested explanation of a phenomenon, or alternately a reasoned
proposal suggesting a possible correlation between or among a set of phenomena.
Normally hypotheses have the form of a mathematical model. Sometimes, but not
always, they can also be formulated as existential statements, stating that some particular
instance of the phenomenon being studied has some characteristic and causal
explanations, which have the general form of universal statements, stating that every
instance of the phenomenon has a particular characteristic.
Scientists are free to use whatever resources they have — their own creativity, ideas from
other fields, induction, Bayesian inference, and so on — to imagine possible explanations
for a phenomenon under study. Charles Sanders Peirce, borrowing a page from Aristotle
(Prior Analytics, 2.25) described the incipient stages of inquiry, instigated by the
"irritation of doubt" to venture a plausible guess, as abductive reasoning. The history of
science is filled with stories of scientists claiming a "flash of inspiration", or a hunch,
which then motivated them to look for evidence to support or refute their idea. Michael
Polanyi made such creativity the centerpiece of his discussion of methodology.
William Glen observes that
the success of a hypothesis, or its service to science, lies not simply in its
perceived "truth", or power to displace, subsume or reduce a predecessor idea, but
perhaps more in its ability to stimulate the research that will illuminate … bald
suppositions and areas of vagueness.[28]
In general scientists tend to look for theories that are "elegant" or "beautiful". In contrast
to the usual English use of these terms, they here refer to a theory in accordance with the
known facts, which is nevertheless relatively simple and easy to handle. Occam's Razor
serves as a rule of thumb for making these determinations.
[edit]
DNA-hypotheses
Linus Pauling proposed that DNA was a triple helix. Francis Crick and James
Watson learned of Pauling's hypothesis, understood from existing data that
Pauling was wrong and realized that Pauling would soon realize his mistake. So
the race was on to figure out the correct structure. Except that Pauling did not
realize at the time that he was in a race! ..3. DNA-predictions
[edit] Predictions from the hypothesis
Any useful hypothesis will enable predictions, by reasoning including deductive
reasoning. It might predict the outcome of an experiment in a laboratory setting or the
observation of a phenomenon in nature. The prediction can also be statistical and only
talk about probabilities.
It is essential that the outcome be currently unknown. Only in this case does the
eventuation increase the probability that the hypothesis be true. If the outcome is already
known, it's called a consequence and should have already been considered while
formulating the hypothesis.
If the predictions are not accessible by observation or experience, the hypothesis is not
yet useful for the method, and must wait for others who might come afterward, and
perhaps rekindle its line of reasoning. For example, a new technology or theory might
make the necessary experiments feasible.
Caption1
====
Caption2
DNA-predictions====
When Watson and Crick hypothesized that DNA was a double helix, Francis
Crick predicted that an X-ray diffraction image of DNA would show an X-shape.
Also in their first paper they predicted that the double helix structure that they
discovered would prove important in biology, writing "It has not escaped our
notice that the specific pairing we have postulated immediately suggests a
possible copying mechanism for the genetic material". ..4. DNA-experiments
[edit] General relativity
Einstein's prediction (1907): Light bends in a gravitational field
Einstein's theory of General Relativity makes several specific predictions about
the observable structure of space-time, such as a prediction that light bends in a
gravitational field and that the amount of bending depends in a precise way on the
strength of that gravitational field. Arthur Eddington's observations made during a
1919 solar eclipse supported General Relativity rather than Newtonian
gravitation.
[edit] Experiments
Main article: Experiments
The control is very important. Once predictions are made, they can be tested by
experiments. If test results contradict predictions, then the hypotheses are called into
question and explanations may be sought. Sometimes experiments are conducted
incorrectly and are at fault. If the results confirm the predictions, then the hypotheses are
considered likely to be correct but might still be wrong and are subject to further testing.
Depending on the predictions, the experiments can have different shapes. It could be a
classical experiment in a laboratory setting, a double-blind study or an archaeological
excavation. Even taking a plane from New York to Paris is an experiment which tests the
aerodynamical hypotheses used for constructing the plane.
Scientists assume an attitude of openness and accountability on the part of those
conducting an experiment. Detailed record keeping is essential, to aid in recording and
reporting on the experimental results, and providing evidence of the effectiveness and
integrity of the procedure. They will also assist in reproducing the experimental results.
Traces of this tradition can be seen in the work of Hipparchus (190-120 BCE), when
determining a value for the precession of the Earth, while controlled experiments can be
seen in the works of Muslim scientists such as Geber (721-815 CE), al-Battani (853–929)
and Alhacen (965-1039).
[edit]
DNA-experiments
Before proposing their model Watson and Crick had previously seen x-ray
diffraction images by Rosalind Franklin, Maurice Wilkins, and Raymond Gosling.
However, they later reported that Franklin initially rebuffed their suggestion that
DNA might be a double helix. Franklin had immediately spotted flaws in the
initial hypotheses about the structure of DNA by Watson and Crick. The X-shape
in X-ray images helped confirm the helical structure of DNA[29]. ..1. DNAcharacterizations
[edit] Evaluation and iteration
[edit] Testing and improvement
The scientific process is iterative. At any stage it is possible that some consideration will
lead the scientist to repeat an earlier part of the process. Failure to develop an interesting
hypothesis may lead a scientist to re-define the subject they are considering. Failure of a
hypothesis to produce interesting and testable predictions may lead to reconsideration of
the hypothesis or of the definition of the subject. Failure of the experiment to produce
interesting results may lead the scientist to reconsidering the experimental method, the
hypothesis or the definition of the subject.
Other scientists may start their own research and enter the process at any stage. They
might adopt the characterization and formulate their own hypothesis, or they might adopt
the hypothesis and deduce their own predictions. Often the experiment is not done by the
person who made the prediction and the characterization is based on experiments done by
someone else. Published results of experiments can also serve as a hypothesis predicting
their own reproducibility.
[edit]
DNA-iterations
After considerable fruitless experimentation, being discouraged by their superior
from continuing, and numerous false starts, Watson and Crick were able to infer
the essential structure of DNA by concrete modeling of the physical shapes of the
nucleotides which comprise it. They were guided by the bond lengths which had
been deduced by Linus Pauling and by Rosalind Franklin's X-ray diffraction
images. ..DNA Example
[edit] Confirmation
Science is a social enterprise, and scientific work tends to be accepted by the community
when it has been confirmed. Crucially, experimental and theoretical results must be
reproduced by others within the science community. Researchers have given their lives
for this vision; Georg Wilhelm Richmann was killed by lightning (1753) when attempting
to replicate the 1752 kite-flying experiment of Benjamin Franklin.[30]
To protect against bad science and fraudulent data, government research granting
agencies like NSF and science journals like Nature and Science have a policy that
researchers must archive their data and methods so other researchers can access it, test
the data and methods and build on the research that has gone before. Scientific data
archiving can be done at a number of national archives in the U.S. or in the World Data
Center.
[edit] Models of scientific inquiry
Main article: Models of scientific inquiry
[edit] Classical model
The classical model of scientific inquiry derives from Aristotle[31], who distinguished the
forms of approximate and exact reasoning, set out the threefold scheme of abductive,
deductive, and inductive inference, and also treated the compound forms such as
reasoning by analogy.
[edit] Pragmatic model
Main article: Pragmatic theory of truth
Charles Peirce (1839-1914) considered scientific inquiry to be a species of the genus
inquiry, which he defined as any means of fixing belief, that is, any means of arriving at a
settled opinion on a matter in question. He observed that inquiry in general begins with a
state of uncertainty and moves toward a state of certainty, sufficient at least to terminate
the inquiry for the time being.
Peirce held that, in practical matters, slow and stumbling ratiocination is not generally to
be automatically preferred over instinct and tradition, and held that scientific method is
best suited to theoretical inquiry. What recommends the specifically scientific method of
inquiry above all others is the fact that it is deliberately designed to arrive, eventually, at
the ultimately most secure beliefs, upon which the most successful actions can eventually
be based.[32] In 1877[33], he outlined four methods for the fixation of belief, the settlement
of doubt, graded by their success in achieving a sound settlement of belief.
1. The method of tenacity -- persisting in that which one is inclined to think.
2. The method of authority -- conformity to a source of ready-made beliefs.
3. The method of congruity or the a priori or the dilettante or "what is agreeable to
reason" -- leading to argumentation that gets finally nowhere.
4. The scientific method.
Peirce characterized scientific method in terms of the uses of inference, and paid special
attention to the generation of explanations. As a question of presuppositions of reasoning,
he defined truth as the correspondence of a sign (in particular, a proposition) to its object
and, pragmatically, not as any actual consensus of any finite community (i.e., such that to
inquire would be to go ask the experts for the answers), but instead as that ideal final
opinion which all reasonable scientific intelligences would reach, sooner or later but still
inevitably, if they pushed investigation far enough[34].In tandem he defined the real as a
true sign's object (be that object a possibility or quality, or an actuality or brute fact, or a
necessity or norm or law), which is what it is independently of any finite community's
opinion and, pragmatically, has dependence only on the ideal final opinion. That is an
opinion as far or near as the truth itself to you or me or any finite community of minds.
Thus his theory of inquiry boils down to "do the science." He characterized the scientific
method as follows[35]:
1. Abduction (or retroduction). Generation of explanatory hypothesis. From abduction,
Peirce distinguishes induction as inferring, on the basis of tests, the proportion of truth in
the hypothesis. Every inquiry, whether into ideas, brute facts, or norms and laws, arises
as a result of surprising observations in the given realm or realms, and the pondering of
the phenomenon in all its aspects in the attempt to resolve the wonder. All explanatory
content of theories is reached by way of abduction, the most insecure among modes of
inference. Induction as a process is far too slow for that job, so economy of research
demands abduction, whose modicum of success depends on one's being somehow attuned
to nature, by dispositions learned and, some of them, likely inborn. Abduction has
general justification inductively in that it works often enough and that nothing else works,
at least not quickly enough when science is already properly rather slow, the work of
indefinitely many generations. Peirce calls his pragmatism "the logic of abduction"[36].
His Pragmatic Maxim is: "Consider what effects that might conceivably have practical
bearings you conceive the objects of your conception to have. Then, your conception of
those effects is the whole of your conception of the object"[34]. His pragmatism is a
method of sorting out conceptual confusions by equating the meaning of any concept
with the conceivable practical consequences of whatever it is which the concept portrays.
It is a method of experimentational mental reflection arriving at conceptions in terms of
conceivable confirmatory and disconfirmatory circumstances -- a method hospitable to
the generation of explanatory hypotheses, and conducive to the employment and
improvement of verification to test the truth of putative knowledge. Given abduction's
dependence on mental processes not necessarily conscious and deliberate but, in any
case, attuned to nature, and given abduction's being driven by the need to economize the
inquiry process, its explanatory hypotheses should be optimally simple in the sense of
"natural" (for which Peirce cites Galileo and which Peirce distinguishes from "logically
simple"). Given abduction's insecurity, it should have consequences with conceivable
practical bearing leading at least to mental tests, and, in science, lending themselves to
scientific testing.
2. Deduction. Analysis of hypothesis and deduction of its consequences in order to test
the hypothesis. Two stages:
i. Explication. Logical analysis of the hypothesis in order to render it as distinct as
possible.
ii. Demonstration (or deductive argumentation). Deduction of hypothesis's
consequence. Corollarial or, if needed, Theorematic.
3. Induction. The long-run validity of the rule of induction is deducible from the
principle (presuppositional to reasoning in general[34]) that the real is only the object of
the final opinion to which adequate investigation would lead[37] In other words, if there
were something to which an inductive process involving ongoing tests or observations
would never lead, then that thing would not be real. Three stages:
i. Classification. Classing objects of experience under general ideas.
ii. Probation (or direct Inductive Argumentation): Crude (the enumeration of
instances) or Gradual (new estimate of proportion of truth in the hypothesis after
each test). Gradual Induction is Qualitative or Quantitative; if Quantitative, then
dependent on measurements, or on statistics, or on countings.
iii. Sentential Induction. "...which, by Inductive reasonings, appraises the different
Probations singly, then their combinations, then makes self-appraisal of these very
appraisals themselves, and passes final judgment on the whole result"[35].
[edit] Computational approaches
Many subspecialties of applied logic and computer science, to name a few, artificial
intelligence, machine learning, computational learning theory, inferential statistics, and
knowledge representation, are concerned with setting out computational, logical, and
statistical frameworks for the various types of inference involved in scientific inquiry, in
particular, hypothesis formation, logical deduction, and empirical testing. Some of these
applications draw on measures of complexity from algorithmic information theory to
guide the making of predictions from prior distributions of experience, for example, see
the complexity measure called the speed prior from which a computable strategy for
optimal inductive reasoning can be derived.
[edit] Philosophy and sociology of science
Main article: Philosophy of science
Further information: Sociology of science
While the philosophy of science has limited direct impact on day-to-day scientific
practice, it plays a vital role in justifying and defending the scientific approach.
Philosophy of science looks at the underpinning logic of the scientific method, at what
separates science from non-science, and the ethic that is implicit in science.
We find ourselves in a world that is not directly understandable. We find that we
sometimes disagree with others as to the facts of the things we see in the world around us,
and we find that there are things in the world that are at odds with our present
understanding. The scientific method attempts to provide a way in which we can reach
agreement and understanding. A "perfect" scientific method might work in such a way
that rational application of the method would always result in agreement and
understanding; a perfect method would arguably be algorithmic, and so not leave any
room for rational agents to disagree. As with all philosophical topics, the search has been
neither straightforward nor simple. Logical Positivist, empiricist, falsificationist, and
other theories have claimed to give a definitive account of the logic of science, but each
has in turn been criticized.
Thomas Samuel Kuhn examined the history of science in his The Structure of Scientific
Revolutions, and found that the actual method used by scientists differed dramatically
from the then-espoused method.
Imre Lakatos and Thomas Kuhn have done extensive work on the "theory laden"
character of observation. Kuhn (1961) said the scientist generally has a theory in mind
before designing and undertaking experiments so as to make empirical observations, and
that the "route from theory to measurement can almost never be traveled backward". This
implies that the way in which theory is tested is dictated by the nature of the theory itself,
which led Kuhn (1961, p. 166) to argue that "once it has been adopted by a profession ...
no theory is recognized to be testable by any quantitative tests that it has not already
passed".
Paul Feyerabend similarly examined the history of science, and was led to deny that
science is genuinely a methodological process. In his book Against Method he argues that
scientific progress is not the result of applying any particular method. In essence, he says
that "anything goes", by which he meant that for any specific methodology or norm of
science, successful science has been done in violation of it. Criticisms such as his led to
the strong programme, a radical approach to the sociology of science.
In his 1958 book, Personal Knowledge, chemist and philosopher Michael Polanyi (18911976) criticized the common view that the scientific method is purely objective and
generates objective knowledge. Polanyi cast this view as a misunderstanding of the
scientific method and of the nature of scientific inquiry, generally. He argued that
scientists do and must follow personal passions in appraising facts and in determining
which scientific questions to investigate. He concluded that a structure of liberty is
essential for the advancement of science - that the freedom to pursue science for its own
sake is a prerequisite for the production of knowledge through peer review and the
scientific method.
The postmodernist critiques of science have themselves been the subject of intense
controversy and heated dialogue. This ongoing debate, known as the science wars, is the
result of the conflicting values and assumptions held by the postmodernist and realist
camps. Whereas postmodernists assert that scientific knowledge is simply another
discourse and not representative of any form of fundamental truth, realists in the
scientific community maintain that scientific knowledge does reveal real and fundamental
truths about reality. Many books have been written by scientists which take on this
problem and challenge the assertions of the postmodernists while defending science as a
legitimate method of deriving truth.[38][39][40][41][42]
[edit] Communication, community, culture
Frequently the scientific method is not employed by a single person, but by several
people cooperating directly or indirectly. Such cooperation can be regarded as one of the
defining elements of a scientific community. Various techniques have been developed to
ensure the integrity of the scientific method within such an environment.
[edit] Peer review evaluation
Scientific journals use a process of peer review, in which scientists' manuscripts are
submitted by editors of scientific journals to (usually one to three) fellow (usually
anonymous) scientists familiar with the field for evaluation. The referees may or may not
recommend publication, publication with suggested modifications, or, sometimes,
publication in another journal. This serves to keep the scientific literature free of
unscientific or crackpot work, helps to cut down on obvious errors, and generally
otherwise improve the quality of the scientific literature. Work announced in the popular
press before going through this process is generally frowned upon. Sometimes peer
review inhibits the circulation of unorthodox work, especially if it undermines the
establishment in the particular field, and at other times may be too permissive. Other
drawbacks includes cronyism and favoritism. The peer review process is not always
successful, but has been very widely adopted by the scientific community.
[edit] Documentation and replication
Sometimes experimenters may make systematic errors during their experiments,
unconsciously veer from the scientific method (Pathological science) for various reasons,
or, in rare cases, deliberately falsify their results. Consequently, it is a common practice
for other scientists to attempt to repeat the experiments in order to duplicate the results,
thus further validating the hypothesis.
[edit] Archiving
As a result, researchers are expected to practice scientific data archiving in compliance
with the policies of government funding agencies and scientific journals. Detailed records
of their experimental procedures, raw data, statistical analyses and source code are
preserved in order to provide evidence of the effectiveness and integrity of the procedure
and assist in reproduction. These procedural records may also assist in the conception of
new experiments to test the hypothesis, and may prove useful to engineers who might
examine the potential practical applications of a discovery.
[edit] Dearchiving
When additional information is needed before a study can be reproduced, the author of
the study is expected to provide it promptly - although a small charge may apply. If the
author refuses to share data, appeals can be made to the journal editors who published the
study or to the institution who funded the research.
[edit] Limitations
Note that it is not possible for a scientist to record everything that took place in an
experiment. He must select the facts he believes to be relevant to the experiment and
report them. This may lead, unavoidably, to problems later if some supposedly irrelevant
feature is questioned. For example, Heinrich Hertz did not report the size of the room
used to test Maxwell's equations, which later turned out to account for a small deviation
in the results. The problem is that parts of the theory itself need to be assumed in order to
select and report the experimental conditions. The observations are hence sometimes
described as being 'theory-laden'.
[edit] Dimensions of practice
Further information: Rhetoric of science
The primary constraints on contemporary western science are:


Publication, i.e. Peer review
Resources (mostly funding)
It has not always been like this: in the old days of the "gentleman scientist" funding (and
to a lesser extent publication) were far weaker constraints.
Both of these constraints indirectly bring in a scientific method — work that too
obviously violates the constraints will be difficult to publish and difficult to get funded.
Journals do not require submitted papers to conform to anything more specific than "good
scientific practice" and this is mostly enforced by peer review. Originality, importance
and interest are more important - see for example the author guidelines for Nature.
Criticisms (see Critical theory) of these restraints are that they are so nebulous in
definition (e.g. "good scientific practice") and open to ideological, or even political,
manipulation apart from a rigorous practice of a scientific method, that they often serve
to censor rather than promote scientific discovery.[citation needed] Apparent censorship
through refusal to publish ideas unpopular with mainstream scientists (unpopular because
of ideological reasons and/or because they seem to contradict long held scientific
theories) has soured the popular perception of scientists as being neutral or seekers of
truth and often denigrated popular perception of science as a whole.
[edit] History
Main article: History of scientific method
See also: Timeline of the history of scientific method
The development of the scientific method is inseparable from the history of science itself.
Ancient Egyptian documents, such as early papyri, describe methods of medical
diagnosis. In ancient Greek culture, the method of empiricism was described. The first
experimental scientific method was developed by Muslim scientists, who introduced the
use of experimentation and quantification to distinguish between competing scientific
theories set within a generally empirical orientation, which emerged with Alhacen's
optical experiments in his Book of Optics (1021).[43][44] The modern scientific method
crystallized no later than in the 17th and 18th centuries. In his work Novum Organum
(1620) — a reference to Aristotle's Organon — Francis Bacon outlined a new system of
logic to improve upon the old philosophical process of syllogism. Then, in 1637, René
Descartes established the framework for a scientific method's guiding principles in his
treatise, Discourse on Method. The writings of Alhacen, Bacon and Descartes are
considered critical in the historical development of the modern scientific method.
In the late 19th century, Charles Sanders Peirce proposed a schema that would turn out to
have considerable influence in the development of current scientific method generally.
Peirce accelerated the progress on several fronts. Firstly, speaking in broader context in
"How to Make Our Ideas Clear" (1878) [3], Peirce outlined an objectively verifiable
method to test the truth of putative knowledge on a way that goes beyond mere
foundational alternatives, focusing upon both deduction and induction. He thus placed
induction and deduction in a complementary rather than competitive context (the latter of
which had been the primary trend at least since David Hume, who wrote in the mid-tolate 18th century). Secondly, and of more direct importance to modern method, Peirce put
forth the basic schema for hypothesis/testing that continues to prevail today. Extracting
the theory of inquiry from its raw materials in classical logic, he refined it in parallel with
the early development of symbolic logic to address the then-current problems in scientific
reasoning. Peirce examined and articulated the three fundamental modes of reasoning
that, as discussed above in this article, play a role in inquiry today, the processes that are
currently known as abductive, deductive, and inductive inference. Thirdly, he played a
major role in the progress of symbolic logic itself — indeed this was his primary
specialty.
Karl Popper denied the existence of evidence[45] and of scientific method.[46] Popper
holds that there is only one universal method, the negative method of trial and error. It
covers not only all products of the human mind, including science, mathematics,
philosophy, art and so on, but also the evolution of life.[47]
[edit] Relationship with mathematics
Science is the process of gathering, comparing, and evaluating proposed models against
observables. A model can be a simulation, mathematical or chemical formula, or set of
proposed steps. Science is like mathematics in that researchers in both disciplines can
clearly distinguish what is known from what is unknown at each stage of discovery.
Models, in both science and mathematics, need to be internally consistent and also ought
to be falsifiable (capable of disproof). In mathematics, a statement need not yet be
proven; at such a stage, that statement would be called a conjecture. But when a
statement has attained mathematical proof, that statement gains a kind of immortality
which is highly prized by mathematicians, and for which some mathematicians devote
their lives[48].
Mathematical work and scientific work can inspire each other[49]. For example, the
concept of time arose in science, and timelessness was a hallmark of a mathematical
topic. But today, the Poincaré conjecture is in the process of being proven, using time as
a mathematical concept, in which objects can flow (see Ricci flow).
George Pólya's work on problem solving[50], the construction of mathematical proofs, and
heuristic[51][52] show that mathematical method and scientific method differ in detail,
while resembling each other in the use of iterative or recursive steps.
Mathematical method
Scientific method
Characterization from experience and observation
1 Understanding
Hypothesis: a proposed explanation
2 Analysis
Deduction: prediction from the hypothesis
3 Synthesis
Test and experiment
4 Review/Extend
In Pólya's view, understanding involves restating unfamiliar definitions in your own
words, resorting to geometrical figures, and questioning what we know and do not know
already; analysis, which Pólya takes from Pappus[53], involves free and heuristic
construction of plausible arguments, working backward from the goal, and devising a
plan for constructing the proof; synthesis is the strict Euclidean exposition of step-by-step
details[54] of the proof; review involves reconsidering and re-examining the result and the
path taken to it.
[edit] Notes and references
1. ^ Isaac Newton (1687, 1713, 1726). "[4] Rules for the study of natural
philosophy", Philosophiae Naturalis Principia Mathematica, Third edition. The
General Scholium containing the 4 rules follows Book 3, The System of the
World. Reprinted on pages 794-796 of I. Bernard Cohen and Anne Whitman's
1999 translation, University of California Press ISBN 0-520-08817-4, 974 pages.
2. ^ scientific method, Merriam-Webster Dictionary.
3. ^ Alhazen (Ibn Al-Haytham) Critique of Ptolemy, translated by S. Pines, Actes X
Congrès internationale d'histoire des sciences, Vol I Ithaca 1962, as referenced
on p. 139 of Shmuel Sambursky (ed. 1974) Physical Thought from the
Presocratics to the Quantum Physicists ISBN 0-87663-712-8
4. ^ Alhazen, translated into English from German by M. Schwarz, from
"Abhandlung über das Licht", J. Baarmann (ed. 1882) Zeitschrift der Deutschen
Morgenländischen Gesellschaft Vol 36 as referenced on p.1 36 by Shmuel
Sambursky (1974) Physical thought from the Presocratics to the Quantum
Physicists ISBN 0-87663-712-8
5. ^ p. 136, as quoted by Shmuel Sambursky (1974) Physical thought from the
Presocratics to the Quantum Physicists ISBN 0-87663-712-8
6. ^ "... the statement of a law - A depends on B - always transcends experience." p.
6 —Max Born (1949), Natural Philosophy of Cause and Chance
7. ^ "I believe that we do not know anything for certain, but everything probably."
—Christiaan Huygens, Letter to Pierre Perrault, 'Sur la préface de M. Perrault de
son traité del'Origine des fontaines' [1763], Oeuvres Complétes de Christiaan
Huygens (1897), Vol. 7, 298. Quoted in Jacques Roger, The Life Sciences in
Eighteenth-Century French Thought, ed. Keith R. Benson and trans. Robert
Ellrich (1997), 163. Quotation selected by W.F. Bynum and Roy Porter (eds.,
2005), Oxford Dictionary of Scientific Quotations ISBN 0-19-858409-1 p. 317
quotation 4.
8. ^ "Observation and experiment are subject to a very popular myth. ... The knower
is seen as a ... Julius Caesar winning his battles according to ... formula. Even
research workers will admit that the first observation may have been a little
imprecise, whereas the second and third were 'adjusted to the facts' ... until
tradition, education, and familiarity have produced a readiness for stylized (that is
directed and restricted) perception and action; until an answer becomes largely
pre-formed in the question, and a decision confined merely to 'yes' or 'no' or
perhaps to a numerical determination; until methods and apparatus automatically
carry out the greatest part of the mental work for us." Fleck labels this thought
style (Denkstil). Ludwik Fleck, p.84 of Genesis and Development of a Scientific
Fact (written in German, 1935, Entstehung und Entwickelung einer
wissenschaftlichen Tatsache: Einführung in die Lehre vom Denkstil und
Denkkollectiv) ISBN 0-226-25325-2
9. ^ See the hypothethico-deductive method, for example: p.236 —Peter GodfreySmith (2003), Theory and Reality: An introduction to the philosophy of science
ISBN 0-226-30063-3
10. ^ pp.265-6 (in the Dover edition) —William Stanley Jevons (1873), The
principles of science: a treatise on logic and scientific method. ISBN 1430487755
11. ^ pp.65,73,92,398 —Andrew J. Galambos, Sic Itur ad Astra ISBN 0-88078-0045(AJG learned scientific method from Felix Ehrenhaft)
12. ^ Galileo Galilei Linceo (1638), Discorsi e Dimonstrazioni Matematiche, intorno
a due nuoue scienze. In Leida, Apresso gli Elsevirri M.D.C.XXXVIII. Two New
Sciences was selected from the collection of the Library of Congress by Leonard
C. Bruno (1988), The Landmarks of Science ISBN 0-8160-2137-6
13. ^ Iteration example: Chaldean astronomers such as Kidinnu compiled
astronomical data. Hipparchus was to use this data to calculate the precession of
the Earth's axis. Fifteen hundred years after Kiddinu, Al-Batani, born in what is
now Turkey, would use the collected data and improve Hipparchus' value for the
precession of the Earth's axis. Al-Batani's value, 54.5 arc-seconds per year,
compares well to the current value of 49.8 arc-seconds per year (26,000 years for
Earth's axis to round the circle of nutation).
14. ^ Recursion example: the Earth is itself a magnet, with its own North and South
Poles William Gilbert (in Latin 1600) De Magnete, or On Magnetism and
Magnetic Bodies. Translated from Latin to English, selection by Forest Ray
Moulton and Justus J. Schifferes (eds., Second Edition 1960) The Autobiography
of Science pp.113-117
15. ^ "The foundation of general physics ... is experience. These ... everyday
experiences we do not discover without deliberately directing our attention to
them. Collecting information about these is observation." —Hans Christian
Ørsted("First Introduction to General Physics" ¶13, part of a series of public
lectures at the University of Copenhagen. Copenhagen 1811, in Danish, printed
by Johan Frederik Schulz. In Kirstine Meyer's 1920 edition of Ørsted's works,
vol.III pp. 151-190. ) "First Introduction to Physics: the Spirit, Meaning, and
Goal of Natural Science". Reprinted in German in 1822, Schweigger's Journal für
Chemie und Physik 36, pp.458-488. Translated to English by Karen Jelved,
Andrew D. Jackson, and Ole Knudsen, (translators 1997) Selected Scientific
Works of Hans Christian Ørsted, ISBN 0-691-04334-5 p. 292
16. ^ "When it is not clear under which law of nature an effect or class of effect
belongs, we try to fill this gap by means of a guess. Such guesses have been given
the name conjectures or hypotheses." —Hans Christian Ørsted(1811) "First
Introduction to General Physics" ¶18. Selected Scientific Works of Hans Christian
Ørsted, ISBN 0-691-04334-5 p.297
17. ^ "In general we look for a new law by the following process. First we guess it.
...", p. 156 —Richard Feynman (1965), The Character of Physical Law ISBN 0262-56003-8
18. ^ "... the statement of a law - A depends on B - always transcends experience."
p.6 —Max Born (1949), Natural Philosophy of Cause and Chance
19. ^ "The student of nature ... regards as his property the experiences which the
mathematican can only borrow. This is why he deduces theorems directly from
the nature of an effect while the mathematician only arrives at them circuitously."
—Hans Christian Ørsted(1811) "First Introduction to General Physics" ¶17.
Selected Scientific Works of Hans Christian Ørsted, ISBN 0-691-04334-5 p.297
20. ^ Salviati speaks: "I greatly doubt that Aristotle ever tested by experiment
whether it be true that two stones, one weighing ten times as much as the other, if
allowed to fall, at the same instant, from a height of, say, 100 cubits, would so
differ in speed that when the heavier had reached the ground, the other would not
have fallen more than 10 cubits." p.61[1] —Galileo (1638), Two New Sciences as
translated from Italian to English by Henry Crew and Alfonso di Salvio (1914). A
more extended quotation is referenced on pp.80-81 by Forest Ray Moulton and
Justus J. Schifferes (eds., Second Edition 1960) The Autobiography of Science
21. ^ In the inquiry-based education paradigm, the stage of "characterization,
observation, definition, …" is more briefly summed up under the rubric of a
Question.
22. ^ "To raise new questions, new possibilities, to regard old problems from a new
angle, requires creative imagination and marks real advance in science." p.92,
Albert Einstein and Leopold Infeld (1938), The Evolution of Physics: from early
concepts to relativity and quanta ISBN 0-671-20156-5
23. ^ Crawford S, Stucki L (1990), "Peer review and the changing research record",
"J Am Soc Info Science", vol. 41, pp 223-228
24. ^ See, e.g., Gauch, Hugh G., Jr., Scientific Method in Practice (2003), esp.
chapters 5-8
25. ^ Cochran W, Crick FHC and Vand V. (1952) "The Structure of Synthetic
Polypeptides. I. The Transform of Atoms on a Helix", Acta Cryst., 5, 581-586.
26. ^ Andreas Vesalius, Epistola, Rationem, Modumque Propinandi Radicis Chynae
Decocti (1546), 141. Quoted and translated in C.D. O'Malley, Andreas Vesalius of
Brussels, (1964), 116. As quoted by W.F. Bynum & Roy Porter (2005), Oxford
Dictionary of Scientific Quotations Andreas Vesalius, 597:1 ISBN 0-19-858409-1
27. ^ Crick, Francis (1994), The Astonishing Hypothesis ISBN 0-684-19431-7 p.20
28. ^ Glen,William (ed.), The Mass-Extinction Debates: How Science Works in a
Crisis, Stanford University Press, Stanford, CA, 1994. ISBN 0-8047-2285-4. pp.
37-38.
29. ^ "The instant I saw the picture my mouth fell open and my pulse began to race."
-- James D. Watson (1968), The Double Helix, page 167. New York: Atheneum,
Library of Congress card number 68-16217. Page 168 shows the X-shaped pattern
of the B-form of DNA, clearly indicating crucial details of its helical structure to
Watson and Crick.
30. ^ See, e.g., Physics Today, Vol. 59, #1, p42. [2]
31. ^ Aristotle, "Prior Analytics", Hugh Tredennick (trans.), pp. 181-531 in Aristotle,
Volume 1, Loeb Classical Library, William Heinemann, London, UK, 1938.
32. ^ Peirce, C.S., "Lectures on Pragmatism", Cambridge, MA, March 26 – May 17,
1903. Reprinted in part, Collected Papers, CP 5.14–212, Eprint. Reprinted with
Introduction and Commentary, Patricia Ann Turisi (ed.), Pragmatism as a
Principle and a Method of Right Thinking: The 1903 Harvard "Lectures on
Pragmatism", State University of New York Press, Albany, NY, 1997. Reprinted,
pp. 133–241, Peirce Edition Project (eds.), The Essential Peirce, Selected
Philosophical Writings, Volume 2 (1893–1913), Indiana University Press,
Bloomington, IN, 1998.
33. ^ Peirce, C.S. (1877), "The Fixation of Belief", Popular Science Monthly, vol. 12,
pp. 1–15. Reprinted (Chance, Love, and Logic, pp. 7-31), (Collected Papers vol.
5, paras. 358–387), (Philosophical Writings of Peirce, pp. 5-22), (Selected
Writings, pp. 91-112), (Writings of Charles S. Peirce: The Chronological Edition,
vol. 3, pp. 242–257), (The Essential Peirce: Volume 1, pp. 109–123), (Peirce on
Signs, pp. 144-159). Eprint. Internet Archive Popular Science Monthly 12.
34. ^ a b c Peirce, C.S. (1877), "How to Make Our Ideas Clear", Popular Science
Monthly, vol. 12, pp. 286–302. Reprinted (Chance, Love, and Logic, pp. 32-60),
(Collected Papers, vol. 5, pp. 388–410), (Philosophical Writings of Peirce, pp.
23-41), (Selected Writings, pp. 113-136), (Writings of Charles S. Peirce: The
Chronological Edition, vol. 3, pp. 257–276), (The Essential Peirce: Volume 1, pp.
124–141), (Peirce on Signs, pp. 160-179). Eprint. Arisbe Eprint. Internet Archive
Popular Science Monthly 12.
35. ^ a b Peirce, C.S. (1908), "A Neglected Argument for the Reality of God", Hibbert
Journal vol. 7, pp. 90-112. Reprinted (Collected Papers, vol. 6, paras. 452-485),
(Selected Writings, pp. 358-379), (The Essential Peirce: Volume 2, 434-450),
(Peirce on Signs, pp. 260-278). Internet Archive Hibbert Journal 7.
36. ^ See "Pragmatism -- The Logic of Abduction", Collected Papers, vol. 5, paras.
195-205, especially para. 196. Eprint.
37. ^ Peirce, C.S., (1878) "The Probability of Induction", Popular Science Monthly,
vol. 12, pp. 705-718. Reprinted (Chance, Love, and Logic, pp. 82-105), (Collected
Papers vol. 2, paras. 669-693), (Philosophical Writings of Peirce, pp. 174-189),
(Writings of Charles S. Peirce: The Chronological Edition, vol. 3, pp. 290-305),
(The Essential Peirce: Volume 1, pp. 155-169). Popular Science Monthly 12
Eprint at Internet Archive.
38. ^ Higher Superstition: The Academic Left and Its Quarrels with Science, The
Johns Hopkins University Press, 1997
39. ^ Fashionable Nonsense: Postmodern Intellectuals' Abuse of Science, Picador; 1st
Picador USA Pbk. Ed edition, 1999
40. ^ The Sokal Hoax: The Sham That Shook the Academy, University of Nebraska
Press, 2000 ISBN 0803279957
41. ^ A House Built on Sand: Exposing Postmodernist Myths About Science, Oxford
University Press, 2000
42. ^ Intellectual Impostures, Economist Books, 2003
43. ^ Rosanna Gorini (2003), "Al-Haytham the Man of Experience, First Steps in the
Science of Vision", International Society for the History of Islamic Medicine,
Institute of Neurosciences, Laboratory of Psychobiology and
Psychopharmacology, Rome, Italy:
"According to the majority of the historians al-Haytham was the
pioneer of the modern scientific method. With his book he changed
the meaning of the term optics and established experiments as the
norm of proof in the field. His investigations are based not on
abstract theories, but on experimental evidences and his
experiments were systematic and repeatable."
44. ^ David Agar (2001). Arabic Studies in Physics and Astronomy During 800 1400 AD. University of Jyväskylä.
45. ^ Logik der Forschung, new appendix *XIX (not yet available in the English
edition Logic of scientific discovery)
46. ^ Karl Popper: On the non-existence of scientific method. Realism and the Aim of
Science (1983)
47. ^ Karl Popper: Objective Knowledge (1972)
48. ^ "When we are working intensively, we feel keenly the progress of our work; we
are elated when our progress is rapid, we are depressed when it is slow." page
131, in the section on 'Modern heuristic'-- the mathematician George Pólya
(1957), How to solve it, Second edition.
49. ^ "Philosophy [i.e., physics] is written in this grand book--I mean the universe-which stands continually open to our gaze, but it cannot be understood unless one
first learns to comprehend the language and interpret the characters in which it is
written. It is written in the language of mathematics, and its characters are
triangles, circles, and other geometrical figures, without which it is humanly
impossible to understand a single word of it; without these, one is wandering
around in a dark labyrinth." —Galileo Galilei, Il Saggiatore (The Assayer, 1623)
as referenced by G. Toraldo di Francia (1981), The Investigation of the Physical
World ISBN 0-521-29925-X
50. ^ George Pólya, How to Solve It
51. ^ George Pólya, Mathematics and Plausible Reasoning Volume I: Induction and
Analogy in Mathematics,
52. ^ George Pólya, Mathematics and Plausible Reasoning Volume II: Patterns of
Plausible Reasoning.
53. ^ George Pólya (1957), How to Solve It Second edition p.142
54. ^ George Pólya (1957), How to Solve It Second edition p.144
[edit] Further reading

Bacon, Francis Novum Organum (The New Organon), 1620. Bacon's work
described many of the accepted principles, underscoring the importance of
theory, empirical results, data gathering, experiment, and independent
corroboration.

Bauer, Henry H., Scientific Literacy and the Myth of the Scientific Method,
University of Illinois Press, Champaign, IL, 1992

Beveridge, William I. B., The Art of Scientific Investigation, Vintage/Alfred
A. Knopf, 1957.

Bernstein, Richard J., Beyond Objectivism and Relativism: Science,
Hermeneutics, and Praxis, University of Pennsylvania Press, Philadelphia,
PA, 1983.

Bozinovski, Stevo, Consequence Driven Systems: Teaching, Learning, and
Self-Learning Agents, GOCMAR Publishers, Bitola, Macedonia, 1991.

Brody, Baruch A., and Grandy, Richard E., Readings in the Philosophy of
Science, 2nd edition, Prentice Hall, Englewood Cliffs, NJ, 1989.

Burks, Arthur W., Chance, Cause, Reason — An Inquiry into the Nature of
Scientific Evidence, University of Chicago Press, Chicago, IL, 1977.

Chomsky, Noam, Reflections on Language, Pantheon Books, New York, NY,
1975.

Dewey, John, How We Think, D.C. Heath, Lexington, MA, 1910. Reprinted,
Prometheus Books, Buffalo, NY, 1991.

Earman, John (ed.), Inference, Explanation, and Other Frustrations: Essays in
the Philosophy of Science, University of California Press, Berkeley & Los
Angeles, CA, 1992.

Fraassen, Bas C. van, The Scientific Image, Oxford University Press, Oxford,
UK, 1980.

Feyerabend, Paul K., Against Method, Outline of an Anarchistic Theory of
Knowledge, 1st published, 1975. Reprinted, Verso, London, UK, 1978.

Gadamer, Hans-Georg, Reason in the Age of Science, Frederick G. Lawrence
(trans.), MIT Press, Cambridge, MA, 1981.

Giere, Ronald N. (ed.), Cognitive Models of Science, vol. 15 in 'Minnesota
Studies in the Philosophy of Science', University of Minnesota Press,
Minneapolis, MN, 1992.

Hacking, Ian, Representing and Intervening, Introductory Topics in the
Philosophy of Natural Science, Cambridge University Press, Cambridge, UK,
1983.

Heisenberg, Werner, Physics and Beyond, Encounters and Conversations,
A.J. Pomerans (trans.), Harper and Row, New York, NY 1971, pp. 63–64.

Holton, Gerald, Thematic Origins of Scientific Thought, Kepler to Einstein,
1st edition 1973, revised edition, Harvard University Press, Cambridge, MA,
1988.

Jevons, William Stanley, The Principles of Science: A Treatise on Logic and
Scientific Method, 1874, 1877, 1879. Reprinted with a foreword by Ernst
Nagel, Dover Publications, New York, NY, 1958.

Kuhn, Thomas S., "The Function of Measurement in Modern Physical
Science", ISIS 52(2), 161–193, 1961.

Kuhn, Thomas S., The Structure of Scientific Revolutions, University of
Chicago Press, Chicago, IL, 1962. 2nd edition 1970. 3rd edition 1996.

Kuhn, Thomas S., The Essential Tension, Selected Studies in Scientific
Tradition and Change, University of Chicago Press, Chicago, IL, 1977.

Latour, Bruno, Science in Action, How to Follow Scientists and Engineers
through Society, Harvard University Press, Cambridge, MA, 1987.

Losee, John, A Historical Introduction to the Philosophy of Science, Oxford
University Press, Oxford, UK, 1972. 2nd edition, 1980.

Maxwell, Nicholas, The Comprehensibility of the Universe: A New
Conception of Science, Oxford University Press, Oxford, 1998. Paperback
2003.

McComas, William F., ed. The Principle Elements of the Nature of Science:
Dispelling the MythsPDF (189 KiB), from The Nature of Science in Science
Education, pp53-70, Kluwer Academic Publishers, Netherlands 1998.

Misak, Cheryl J., Truth and the End of Inquiry, A Peircean Account of Truth,
Oxford University Press, Oxford, UK, 1991.

Newell, Allen, Unified Theories of Cognition, Harvard University Press,
Cambridge, MA, 1990.

Peirce, C.S., Essays in the Philosophy of Science, Vincent Tomas (ed.),
Bobbs–Merrill, New York, NY, 1957.

Peirce, C.S., "Lectures on Pragmatism", Cambridge, MA, March 26 – May
17, 1903. Reprinted in part, Collected Papers, CP 5.14–212. Reprinted with
Introduction and Commentary, Patricia Ann Turisi (ed.), Pragmatism as a
Principle and a Method of Right Thinking: The 1903 Harvard "Lectures on
Pragmatism", State University of New York Press, Albany, NY, 1997.
Reprinted, pp. 133–241, Peirce Edition Project (eds.), The Essential Peirce,
Selected Philosophical Writings, Volume 2 (1893–1913), Indiana University
Press, Bloomington, IN, 1998.

Peirce, C.S., Collected Papers of Charles Sanders Peirce, vols. 1-6, Charles
Hartshorne and Paul Weiss (eds.), vols. 7-8, Arthur W. Burks (ed.), Harvard
University Press, Cambridge, MA, 1931-1935, 1958. Cited as CP vol.para.

Piattelli-Palmarini, Massimo (ed.), Language and Learning, The Debate
between Jean Piaget and Noam Chomsky, Harvard University Press,
Cambridge, MA, 1980.

Poincaré, Henri, Science and Hypothesis, 1905, Eprint

Popper, Karl R., The Logic of Scientific Discovery, 1934, 1959.[4]

Popper, Karl R., Unended Quest, An Intellectual Autobiography, Open Court,
La Salle, IL, 1982.

Putnam, Hilary, Renewing Philosophy, Harvard University Press, Cambridge,
MA, 1992.

Rorty, Richard, Philosophy and the Mirror of Nature, Princeton University
Press, Princeton, NJ, 1979.

Salmon, Wesley C., Four Decades of Scientific Explanation, University of
Minnesota Press, Minneapolis, MN, 1990.

Shimony, Abner, Search for a Naturalistic World View: Vol. 1, Scientific
Method and Epistemology, Vol. 2, Natural Science and Metaphysics,
Cambridge University Press, Cambridge, UK, 1993.

Thagard, Paul, Conceptual Revolutions, Princeton University Press, Princeton,
NJ, 1992.

Ziman, John (2000). Real Science: what it is, and what it means. Cambridge,
Uk: Cambridge University Press.
[edit] See also


Baconian method
Empirical method
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Historical method
Philosophical method
Quantitative research
Scholarly method
[edit] Synopsis of related topics
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Confirmability
Contingency
Falsifiability
Hypothesis
Hypothesis testing
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Inquiry
Reproducibility
Research
Statistics
Strong inference
Tautology
Testability
Theory
Verification and
Validation
[edit] Logic, mathematics, methodology





Inference
o Abductive reasoning
o Deductive reasoning
o Inductive reasoning
Information theory
Logic
Mathematics
Methodology
[edit] Problems and issues
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Ockham's razor
Poverty of the stimulus
Reference class problem
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[edit] History, philosophy, sociology
Underdetermination
Holistic science
Pseudoscience
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Cudos
Epistemology
Epistemic truth
History of science
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History of scientific
method
Philosophy of
science
Science studies
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
Social research
Sociology of
scientific
knowledge
Timeline of
scientific method
[edit] External links
Wikibooks has a book on the topic of
The Scientific Method

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
An Introduction to Science: Scientific Thinking and a scientific method by Steven
D. Schafersman.
Introduction to a scientific method
Theory-ladenness by Paul Newall at The Galilean Library
Lecture on Scientific Method by Greg Anderson
Using the scientific method for designing science fair projects
SCIENTIFIC METHODS an online book by Richard D. Jarrard
Introduction to the Scientific Method

Introduction to the Scientific Method
o I. The scientific method has four steps
o II. Testing hypotheses
o III. Common Mistakes in Applying the Scientific Method
o IV. Hypotheses, Models, Theories and Laws
o V. Are there circumstances in which the Scientific Method is not
applicable?
o VI. Conclusion
o VII. References
Introduction to the Scientific Method
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, the scientific method attempts to minimize the
influence of bias or prejudice in the experimenter when testing an hypothesis or a theory.
I. The scientific method has four steps
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.
II. Testing hypotheses
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.
III. Common Mistakes in Applying the Scientific Method
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.
V. Are there circumstances in which the Scientific Method is not
applicable?
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.
VI. Conclusion
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.
VII. References
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).
SCIENTIFIC METHODS
an online book
Richard D. Jarrard
Dept. of Geology and Geophysics, University of Utah
u0035311@umail.utah.edu
© Richard D. Jarrard 2001
Scientific Methods is an online book about the techniques and processes of science and
the experience of being a scientist. This book is written by a scientist for scientists. My
hope is that it will be browsed by scientists (including graduate students) and read by
undergraduates.
Why am I publishing this book online, despite having a willing soft-cover publisher? The
main reason is wider availability to readers. A typical science book has a publication run
of ~2000 copies, then it goes out of print. Additional factors include educational use and
ease of revision. I admit that I would have enjoyed saying that I earned ~25¢/hour by
writing this book.
Below the Table of Contents are Adobe Acrobat PDF files, which are more printerfriendly than the web pages. The PDF files also include a Name Index and Subject Index.
Feel free to print a personal copy. Note, however, that this book is copyrighted; it is
unethical (see Chapter 10) and illegal to distribute multiple printouts or digital copies or
to copy any of these files to other web sites.
CONTENTS
1. Introduction
Overview
Thumbnail History of Scientific Methods
Myth of a Scientific Method
Scientific Methods
SCIENTIFIC TOOLBOX
2. Variables
Statistics
Errors
Precision > Accuracy > Reliability
Random and Systematic Errors
Representative Sampling
Replication and Confirmation
Probability
Sampling Distribution for One Variable
Histograms
Normal Distribution
Mean & Standard Deviation
Normal Distribution Function
Weighted Mean
95% Confidence Limits on Mean
How Many Measurements are Needed?
Propagation of Errors
Non-Normal Distributions
Normality Tests
Rejecting Anomalous Data
Median, Range, & 95% Confidence Limits
Examples
3. Induction and Pattern Recognition
Types of Explanation
Coincidence
Correlation
Examples
Crossplots
Plotting Hints
Extrapolation and Interpolation
Correlation Statistics
Nonlinear Relationships
Correlation Conclusions
Perspectives on Causality
Mill's Canons: Five Inductive Methods
Method of Agreement
Method of Difference
Joint Method of Agreement & Difference
Method of Concomitant Variations
Method of Residues
Correlation or Causality?
4. Deduction and Logic
Logic
Deduction vs. Induction
Deductive Logic
Classification Statements
Deductive Aids: Venn Diagrams and Substitution
Logically Equivalent Statements
Relationships among Statements
Syllogisms
Categorical Syllogisms
Hypothetical Syllogisms
Pitfalls: Fallacious Arguments
Fallacies Resulting from Problems in a Premise
Fallacies Employing Extraneous Other Evidence
Faulty Link between Premises & Conclusion
Case-dependent Relationship between Parts & Whole
5. Experimental Techniques
Observational versus Experimental Science
Seizing an Opportunity
Experimental Equipment
Prototypes and Pilot Studies
Troubleshooting and Search Procedures
Problem: Find a Needle in a Haystack
Problem: Search for the Top Quark
Tips on Experimental Design and Execution
Pitfalls of Experimental Design
Control of Variables
Problem: the Noisy Widgetometer
Computation and Information Handling
LIVING SCIENCE
6. The Myth of Objectivity
Perception: Case Studies
Perception, Memory, and Schemata
Postmodernism
Pitfalls of Subjectivity
Experimental Design
Experiment Execution
Data Interpretation
Publication
Pitfall Examples
Group Objectivity
7. Evidence Evaluation and Scientific Progress
Judgment Values
Evaluation Aids
Confirmation and Refutation of Hypotheses
Power of Evidence
Hypothesis Modification
Paradigm and Scientific Revolution
Pitfalls of Evidence Evaluation
Hidden Influence of Prior Theory on Evidence Evaluation
Incremental Hypotheses and Discoveries
'Fight or Flight' Reaction to New Ideas
Confusing the Package and Product
Pitfall Examples
8. Insight
Role of Insight in Science
Characteristics of Insight
Conditions Favoring Insight
Obstacles to Insight
The Royal Way
How Does Insight Work?
Alternative Paths to Insight
Unexpected Results
Transfer from other Disciplines
Breakthroughs by Amateurs: the Outsider Perspective
From Puzzle Solving …
… To Mystical Experience
9. The Scientist's World
Scientist and Lay Person
Science and Society
Science and the Arts
Science and Pseudoscience
Applied and Basic Research
Conflict: Applied vs. Basic Research
Changing Goals for Applied and Basic Research
Resolution: Bridging the Gap
Big Science versus Little Science
Ego and the Scientific Pecking Order
10. The Scientist
Scientists' Characteristics
Essential Characteristics
Common Characteristics
Cooperation or Competition?
Science Ethics
Publication
A Scientist's Life: Changing Motivations
Process and Product
References
PDF FILES
Table of Contents
1. Introduction
2. Variables
3. Induction and Pattern Recognition
4. Deduction and Logic
5. Experimental Techniques
6. The Myth of Objectivity
7. Evidence Evaluation and Scientific Progress
8. Insight
9. The Scientist's World
10. The Scientist
References
Name Index
Subject Index
PDF of entire book (2.2 MB)