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Read the following passage. Highlight the key terms and underline
the main ideas.
It is one thing to describe and measure the growth of a plant toward light
(discovery science). But what causes this phenomenon? How can scientists
explain the plant's ability to detect and respond to the direction of light? Such
questions about causes and explanations are at the center of hypothesis-based
science.
Methods of Hypothesis-Based Science
You may have heard of "the scientific method." The steps of this idealized
method are diagrammed in Figure 2-10. At one time or another in their research,
scientists may use all or most of these steps. Often, however, the sequence of
steps does not exactly match the generalized scheme of Figure 2-10. For
example, a scientist may start to plan an experiment, but then decide that more
observations are needed first. In other cases, observations are too puzzling to
even suggest key questions until other lines of research bring more
understanding. Or, at some point in a research project, scientists may realize they
have been "barking up the wrong tree." That is, they've been asking the wrong
questions. Many scientific inquiries are abandoned before any questions are
answered, though the data from observations and experiments may prove useful
later. And accidental discoveries, such as Fleming's findings about mold and
bacteria, are certainly not products of a rigid, step-by-step scientific method.
Science is actually less structured than most people realize.
Figure 2-10
Although science rarely matches this step-by-step
process exactly, scientific inquiry often includes the
posing and testing of hypotheses.
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Despite all the variation in scientific inquiry, one key element is common to all
hypothesis-based science. In fact, this form of inquiry is named for this key
element: the hypothesis.
Forming and Testing a Hypothesis
A hypothesis (plural, hypotheses) is a suggested answer to a well-defined
scientific question—an explanation on trial. Most hypotheses are concerned with
the causes of natural phenomena, such as the growth of a plant toward light. A
hypothesis is often based on past experience or knowledge gained from
discovery science or other sources.
People use hypotheses almost instinctively, as a natural way to solve everyday
problems. For example, suppose your flashlight stops working during a camping
trip. That's an observation. The question is obvious: Why doesn't the flashlight
work? A reasonable hypothesis based on past experience is that the batteries in
the flashlight are dead.
Scientists don't just propose hypotheses. They test these ideas by making
additional observations or by designing experiments. A hypothesis allows you to
make certain predictions. It is these predictions that scientists then test. Consider
the case of the failed flashlight in Figure 2-11. Note that the prediction is written
as an "If . . . , then . . ." statement. If a particular hypothesis is correct, and you
test that hypothesis with a suitable experiment, then you should expect a certain
result for the experiment.
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Figure 2-11
Applying hypothesis-based science to the problem of a failed flashlight
leads to a test in the form of an experiment. If the results of the test do not
support the hypothesis, other hypotheses can be suggested and tested.
What if the flashlight still doesn't work after changing the batteries? Here's where
things get interesting. Keep in mind that in science, an incorrect hypothesis
doesn't mean failure. It just means the hypothesis that led to the prediction was
probably wrong. The inquiry continues with tests of alternative hypotheses. What
would be your next step in the flashlight problem? Perhaps, you could test
another hypothesis by replacing the flashlight's bulb.
Even when experiments support a hypothesis, curiosity can send you in new
directions. (How long do batteries last in a flashlight? Do some brands of
batteries last longer than others?) Opportunities for creativity and new challenges
make scientific inquiry as exciting as exploring a new landscape. As you reach
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the top of a hill or round the corner of a trail, you may become curious to see the
view from the next hill or around the next corner. Science generates new
questions in a similar manner.
A Case Study of Hypothesis-Based Science
One way to learn more about how hypothesis-based science works is to examine
a case study. In contrast to a made-up example, such as the flashlight problem, a
case study is an in-depth examination of something that actually happened. For
instance, students in law school train to become lawyers by analyzing the actual
documents of past legal cases. Similarly, a case study of a research project that
was published in a scientific journal will boost your understanding of how
scientists go about their work. The rest of this section is a case study of an
inquiry about what harmless snakes might gain by imitating poisonous ones.
From Observations to Question and Hypothesis The story begins with
some key observations. (Do you recognize this step as discovery science?) Many
poisonous animals are brightly colored, with distinctive patterns in some species.
This appearance is called warning coloration because it marks the animal as
dangerous to potential predators. But there are also mimics. These imposters look
like a poisonous species but are really harmless to predators. For example, a nonstinging insect called the flower fly is very similar in appearance to a stinging
honeybee. The question that follows from these observations is: What is the
function of such mimicry?
In 2001, a team of biologists designed a simple but clever set of experiments to
test a hypothesis that was first suggested over a century earlier. Here's the
hypothesis: Mimics (such as the flower fly) benefit because predators confuse
them with the actual harmful species. Researchers David and Karin Pfennig,
along with one of their college students, tested this hypothesis by studying
mimicry in snakes that live in North and South Carolina. A poisonous snake
called the eastern coral snake is marked by rings of red, yellow, and black.
Predators rarely attack these snakes. A nonpoisonous snake named the scarlet
kingsnake mimics the ringed coloration of the coral snake.
Testing a Prediction of the Hypothesis What is the explanation for this
case of look-alike snakes? According to the mimicry hypothesis, the coralsnakelike appearance of kingsnakes repels predators. The hypothesis predicts that
predators will attack snakes with the bright rings of red, yellow, and black less
frequently than they will attack snakes lacking such warning coloration. To test
this prediction, the researchers made hundreds of artificial kingsnakes out of wire
and a claylike substance called plasticine. There were two types of artificial
snakes: those with the red, yellow, and black ring pattern of coral snakes; and
snakes with plain brown coloration.
The researchers placed equal numbers of the two types of artificial snakes in
various sites throughout North and South Carolina. After four weeks, the team
retrieved the artificial snakes and counted how many had been attacked by
looking for bite or claw marks. The most common predators were foxes, coyotes,
and raccoons, but black bears also attacked some of the artificial snakes.
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Designing a Controlled Experiment Why did the experiment include
artificial snakes that were plain brown along with the ringed snakes? A quick
answer is that the contrast in coloration was necessary to see if predators attack
snakes based on their color. If all the snakes were the same, the number of
attacks would indicate nothing at all about the effect of the colored rings. This
point illustrates an important requirement for designing experiments that test
hypotheses. If you want to test the effect of one condition, you need to provide a
contrasting condition as well. A condition that can differ within the experiment is
called a variable. In the artificial snakes, the variable is the presence versus the
absence of the colored rings. Most often, experiments test the effect of a
difference in just one variable. An experiment that tests the effect of a single
variable is called a controlled experiment.
By conducting a controlled experiment, scientists try to eliminate (control) other
variables that could affect the outcome. This is not usually a simple task. For
example, variables such as temperature or other weather conditions could
influence the activities of predators in the snake experiment. In an ideal setting—
such as a laboratory—scientists can keep temperature and other environmental
conditions as constant as possible. But such control is usually impossible in a
field experiment. And even in a laboratory, total regulation of all but one variable
is often not practical.
Eliminating Unwanted Variables What is the solution to the problem of
unwanted variables? Researchers divide the subjects (the artificial snakes, for
example) into two groups: a control group and an experimental group. Since the
snake experiment was designed to test the effect of the colored rings, the
artificial snakes with the colored rings were the experimental group. The brown
snakes served as a control group by showing what happens in the absence of
colored rings. Everything else about the two snake groups was the same. For
example, both ringed snakes and brown snakes were made of the same materials.
Both kinds of snakes were placed at random in the same locations. Conditions
such as light, temperature, and appetite of the predators varied, but both kinds of
snakes were subject to the same variations. In this way, the brown snakes
controlled, or cancelled out, the effects of the unwanted variables, leaving
colored rings as the only consistent difference between the two groups of snakes.
Then any difference in the number of attacks on the ringed snakes compared to
the brown snakes could only have been due to the difference in coloration.
"If . . . , then . . ." Reasoning You should now be able to recognize in this
case study the same type of reasoning you learned about in the flashlight
example. Using the flowchart in Figure 2-15, you can follow the steps taken by
the Pfennig team. Observations of snake coloration and attacks by predators led
to a question. The Pfennigs posed a hypothesis that seemed reasonable based on
other scientists' past research on different animal species. The Pfennigs then
designed and performed a controlled experiment to test their hypothesis. The
next step was analyzing the data.
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Figure 2-15
This flowchart summarizes the inquiry
process followed during the snake mimicry
research.
Organizing Data and Interpreting Results Scientific inquiry is far from
over once the data have been collected. Often, the results of an experiment only
begin to make sense after much analysis of the data. For quantitative data, note
again that it is often helpful to put the data in the form of a table or graph. These
efforts may reveal patterns that were not obvious when the "raw" data were first
collected.
The bar graph in Figure 2-16 summarizes the results of the artificial snake
experiment. The graph also reinforces the purpose of using two groups of snakes.
Of all attacks on artificial snakes, about 84 percent of attacks were on the plain
brown snakes compared to about 16 percent for the snakes with colored rings.
These data fit the prediction based on the mimicry hypothesis. The experiment
supports the hypothesis that the kingsnakes' mimicry of coral-snake coloration
helps protect against predators.
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Figure 2-16
Results of mimicry experiments using artificial snakes show
a dramatic difference in the frequency of attacks on plain
brown snakes compared to the snakes with colored rings.
The research on look-alike snakes provides an example of how scientists use
hypothesis-based science to test their explanation of natural phenonena. Notice
again how hypothesis-based science works along with discovery science.
Questions about nature usually arise from the observations of discovery science.
Hypothesis-based science is a process for testing the possible answers to such
questions.
The upcoming section broadens the view of science you've seen so far, showing
how scientific ideas fit in with other ways of picturing and knowing the world
around you.
Concept Check 2.2
1. Write a hypothesis to explain why a door hinge squeaks. Then use your
hypothesis to make a prediction that could be tested.
2. Why do experiments usually test only one variable at a time?
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3. In the snake experiment, what was the basis for the hypothesis that mimic
species benefit from looking like unrelated harmful species?
4. What role did the brown artificial snakes have in the experiment?