Patterns and Relationships
Unity of Ideas
Interaction of Theory and Applications
Universality of Mathematics
Science and Mathematics
Mathematics and Technology
Abstraction and Symbolic Representation
Manipulating Mathematical Statements
Application
Chapter 2: THE NATURE OF MATHEMATICS
Mathematics relies on both logic and creativity, and it is pursued both
for a variety of practical purposes and for its intrinsic interest. For
some people, and not only professional mathematicians, the essence of mathematics
lies in its beauty and its intellectual challenge. For others, including
many scientists and engineers, the chief value of mathematics is how it
applies to their own work. Because mathematics plays such a central role
in modern culture, some basic understanding of the nature of mathematics
is requisite for scientific literacy. To achieve this, students need to
perceive mathematics as part of the scientific endeavor, comprehend the
nature of mathematical thinking, and become familiar with key mathematical
ideas and skills.
This chapter focuses on mathematics as part of the scientific endeavor
and then on mathematics as a process, or way of thinking. Recommendations
related to mathematical ideas are presented in Chapter 9, The Mathematical
World, and those on mathematical skills are included in Chapter 12, Habits
of Mind.
PATTERNS AND RELATIONSHIPS
Patterns and Relationships
Mathematics is the science of patterns and relationships. As a theoretical
discipline, mathematics explores the possible relationships among abstractions
without concern for whether those abstractions have counterparts in the
real world. The abstractions can be anything from strings of numbers to
geometric figures to sets of equations. In addressing, say, "Does the interval
between prime numbers form a pattern?" as a theoretical question, mathematicians
are interested only in finding a pattern or proving that there is none,
but not in what use such knowledge might have. In deriving, for instance,
an expression for the change in the surface area of any regular solid as
its volume approaches zero, mathematicians have no interest in any correspondence
between geometric solids and physical objects in the real world.
Unity of Ideas
A central line of investigation in theoretical mathematics is identifying
in each field of study a small set of basic ideas and rules from which
all other interesting ideas and rules in that field can be logically deduced.
Mathematicians, like other scientists, are particularly pleased when previously
unrelated parts of mathematics are found to be derivable from one another,
or from some more general theory. Part of the sense of beauty that many
people have perceived in mathematics lies not in finding the greatest elaborateness
or complexity but on the contrary, in finding the greatest economy and
simplicity of representation and proof. As mathematics has progressed,
more and more relationships have been found between parts of it that have
been developed separately—for example, between the symbolic representations
of algebra and the spatial representations of geometry. These crossconnections
enable insights to be developed into the various parts; together, they
strengthen belief in the correctness and underlying unity of the whole
structure.
Interaction of Theory and Applications
Mathematics is also an applied science. Many mathematicians focus their
attention on solving problems that originate in the world of experience.
They too search for patterns and relationships, and in the process they
use techniques that are similar to those used in doing purely theoretical
mathematics. The difference is largely one of intent. In contrast to theoretical
mathematicians, applied mathematicians, in the examples given above, might
study the interval pattern of prime numbers to develop a new system for
coding numerical information, rather than as an abstract problem. Or they
might tackle the area/volume problem as a step in producing a model for
the study of crystal behavior.
The results of theoretical and applied mathematics often influence each
other. The discoveries of theoretical mathematicians frequently turn out—sometimes
decades later—to have unanticipated practical value. Studies on the mathematical
properties of random events, for example, led to knowledge that later made
it possible to improve the design of experiments in the social and natural
sciences. Conversely, in trying to solve the problem of billing longdistance
telephone users fairly, mathematicians made fundamental discoveries about
the mathematics of complex networks. Theoretical mathematics, unlike the
other sciences, is not constrained by the real world, but in the long run
it contributes to a better understanding of that world.
MATHEMATICS, SCIENCE,
AND TECHNOLOGY
Universality of Mathematics
Because of its abstractness, mathematics is universal in a sense that other
fields of human thought are not. It finds useful applications in business,
industry, music, historical scholarship, politics, sports, medicine, agriculture,
engineering, and the social and natural sciences. The relationship between
mathematics and the other fields of basic and applied science is especially
strong. This is so for several reasons, including the following:
Science and Mathematics

The alliance between science and mathematics has a long history, dating
back many centuries. Science provides mathematics with interesting problems
to investigate, and mathematics provides science with powerful tools to
use in analyzing data. Often, abstract patterns that have been studied
for their own sake by mathematicians have turned out much later to be very
useful in science. Science and mathematics are both trying to discover
general patterns and relationships, and in this sense they are part of
the same endeavor.

Mathematics is the chief language of science. The symbolic language of
mathematics has turned out to be extremely valuable for expressing scientific
ideas unambiguously. The statement that a=F/m is not simply
a shorthand way of saying that the acceleration of an object depends on
the force applied to it and its mass; rather, it is a precise statement
of the quantitative relationship among those variables. More important,
mathematics provides the grammar of science—the rules for analyzing scientific
ideas and data rigorously.

Mathematics and science have many features in common. These include a belief
in understandable order; an interplay of imagination and rigorous logic;
ideals of honesty and openness; the critical importance of peer criticism;
the value placed on being the first to make a key discovery; being international
in scope; and even, with the development of powerful electronic computers,
being able to use technology to open up new fields of investigation.
Mathematics and Technology

Mathematics and technology have also developed a fruitful relationship
with each other. The mathematics of connections and logical chains, for
example, has contributed greatly to the design of computer hardware and
programming techniques. Mathematics also contributes more generally to
engineering, as in describing complex systems whose behavior can then be
simulated by computer. In those simulations, design features and operating
conditions can be varied as a means of finding optimum designs. For its
part, computer technology has opened up whole new areas in mathematics,
even in the very nature of proof, and it also continues to help solve previously
daunting problems.
MATHEMATICAL INQUIRY
Using mathematics to express ideas or to solve problems involves at least
three phases: (1) representing some aspects of things abstractly, (2) manipulating
the abstractions by rules of logic to find new relationships between them,
and (3) seeing whether the new relationships say something useful about
the original things.
Abstraction and Symbolic Representation
Mathematical thinking often begins with the process of abstraction—that
is, noticing a similarity between two or more objects or events. Aspects
that they have in common, whether concrete or hypothetical, can be represented
by symbols such as numbers, letters, other marks, diagrams, geometrical
constructions, or even words. Whole numbers are abstractions that represent
the size of sets of things and events or the order of things within a set.
The circle as a concept is an abstraction derived from human faces, flowers,
wheels, or spreading ripples; the letter A may be an abstraction for the
surface area of objects of any shape, for the acceleration of all moving
objects, or for all objects having some specified property; the symbol
+ represents a process of addition, whether one is adding apples or oranges,
hours, or miles per hour. And abstractions are made not only from concrete
objects or processes; they can also be made from other abstractions, such
as kinds of numbers (the even numbers, for instance).
Such abstraction enables mathematicians to concentrate on some features
of things and relieves them of the need to keep other features continually
in mind. As far as mathematics is concerned, it does not matter whether
a triangle represents the surface area of a sail or the convergence of
two lines of sight on a star; mathematicians can work with either concept
in the same way. The resulting economy of effort is very useful—provided
that in making an abstraction, care is taken not to ignore features that
play a significant role in determining the outcome of the events being
studied.
Manipulating Mathematical Statements
After abstractions have been made and symbolic representations of them
have been selected, those symbols can be combined and recombined in various
ways according to precisely defined rules. Sometimes that is done with
a fixed goal in mind; at other times it is done in the context of experiment
or play to see what happens. Sometimes an appropriate manipulation can
be identified easily from the intuitive meaning of the constituent words
and symbols; at other times a useful series of manipulations has to be
worked out by trial and error.
Typically, strings of symbols are combined into statements that express
ideas or propositions. For example, the symbol A for the area of
any square may be used with the symbol s for the length of the square's
side to form the proposition A = s^{2}. This equation
specifies how the area is related to the side—and also implies that it
depends on nothing else. The rules of ordinary algebra can then be used
to discover that if the length of the sides of a square is doubled, the
square's area becomes four times as great. More generally, this knowledge
makes it possible to find out what happens to the area of a square no matter
how the length of its sides is changed, and conversely, how any change
in the area affects the sides.
Mathematical insights into abstract relationships have grown over thousands
of years, and they are still being extended—and sometimes revised. Although
they began in the concrete experience of counting and measuring, they have
come through many layers of abstraction and now depend much more on internal
logic than on mechanical demonstration. In a sense, then, the manipulation
of abstractions is much like a game: Start with some basic rules, then
make any moves that fit those rules—which includes inventing additional
rules and finding new connections between old rules. The test for the validity
of new ideas is whether they are consistent and whether they relate logically
to the other rules.
Application
Mathematical Modeling
Mathematical processes can lead to a kind of model of a thing, from
which insights can be gained about the thing itself. Any mathematical relationships
arrived at by manipulating abstract statements may or may not convey something
truthful about the thing being modeled. For example, if 2 cups of water
are added to 3 cups of water and the abstract mathematical operation 2+3
= 5 is used to calculate the total, the correct answer is 5 cups of water.
However, if 2 cups of sugar are added to 3 cups of hot tea and the same
operation is used, 5 is an incorrect answer, for such an addition actually
results in only slightly more than 4 cups of very sweet tea. The simple
addition of volumes is appropriate to the first situation but not to the
second—something that could have been predicted only by knowing something
of the physical differences in the two situations. To be able to use and
interpret mathematics well, therefore, it is necessary to be concerned
with more than the mathematical validity of abstract operations and to
also take into account how well they correspond to the properties of the
things represented.
Evaluating Results
Sometimes common sense is enough to enable one to decide whether the
results of the mathematics are appropriate. For example, to estimate the
height 20 years from now of a girl who is 5' 5" tall and growing at the
rate of an inch per year, common sense suggests rejecting the simple "rate
times time" answer of 7' 1" as highly unlikely, and turning instead to
some other mathematical model, such as curves that approach limiting values.
Sometimes, however, it may be difficult to know just how appropriate mathematical
results are—for example, when trying to predict stockmarket prices or
earthquakes.
Often a single round of mathematical reasoning does not produce satisfactory
conclusions, and changes are tried in how the representation is made or
in the operations themselves. Indeed, jumps are commonly made back and
forth between steps, and there are no rules that determine how to proceed.
The process typically proceeds in fits and starts, with many wrong turns
and dead ends. This process continues until the results are good enough.
But what degree of accuracy is good enough? The answer depends on how
the result will be used, on the consequences of error, and on the likely
cost of modeling and computing a more accurate answer. For example, an
error of 1 percent in calculating the amount of sugar in a cake recipe
could be unimportant, whereas a similar degree of error in computing the
trajectory for a space probe could be disastrous. The importance of the
"good enough" question has led, however, to the development of mathematical
processes for estimating how far off results might be and how much computation
would be required to obtain the desired degree of accuracy.