THE SCIENTIFIC METHOD AND CRITICAL THINKING
FOR THE NEXT CLASS DO THE FOLLOWING:
1. Read the following about the scientific method.
2. Design a simple experimental study that could be done about a
subject related to your major or that you’re interested in, using
the scientific method. Remember that the rest of the class may
not be familiar with technical concepts, so keep it simple.
3. Be ready to tell the class what your study would involve,
including all of the following:
hypothesis independent variable
dependent variable treatment group
control group pre-test
4. Be ready to identify the items from #3 in studies other students
THE SCIENTIFIC METHOD AND CRITICAL THINKING
In your everyday life you act as a kind of scientist. You observe the world around
you. You make predictions about how one event will affect another. You develop
explanations for what happens around you. When something unexpected happens you try
to figure out why.
For example, when you meet a new person you pay attention to the way he or she
responds to what you say and do. Based on those observations you predict how he or she
will respond to something you are about to say. If the response is what you expect your
prediction is confirmed. If the response is not what you expect you think of an
explanation. If you continue to interact with that person you continue to observe
behaviors and reactions, compare them to past experiences, make more predictions, and
develop a better understanding of how that individual will react to various actions.
Or you might have a job that calls for you to determine how to best accomplish a
task. Based on what you’ve learned in classes and your personal experience you may
decide that one procedure is more likely to have a positive outcome than the other. If
someone were to ask you why you believe that you’d provide an explanation of how the
different procedures work and why you predict that one would be better than the other.
Most of us are not very systematic as we do our everyday science. We don’t do
our observations very carefully. We make rather vague predictions. Our explanations
often don’t account for all the factors that may be involved. We do well enough to get by
day-to-day but we also commonly jump to conclusions supported by questionable
Over the years scientists and philosophers have developed procedures that are
designed to overcome common problems in gathering evidence and drawing conclusion.
Those procedures are referred to as the scientific method. An understanding of the basics
of the scientific method is helpful to understanding how principles of critical thinking,
reasoning, and argumentation can be applied. While most of us will rarely have the
opportunity to take the time to fully use the scientific method in our everyday lives, the
knowledge of the method can help us improve our daily reasoning.
Understanding basic scientific methodology is also helpful to you as a critical
thinker because you will be confronted with scientific findings throughout your life.
You’ll read or listen to news reports about health and medical discoveries, environmental
findings, social and psychological conclusions, and information from various areas of the
physical and social sciences. You’ll also hear about all sorts of claims about things that
could be verified using scientific techniques but haven’t been examined. There will
probably be times when you make personal decisions such as changing your diet or
supporting some cause based on such news reports, and you’ll have to decide how much
you can believe about them. You may also find yourself in a career in which you will
have to make decisions based on information that is gathered scientifically and you’ll
have to evaluate such information even though you are not a scientist yourself.
In this chapter I will describe the basics of the scientific method and how the
procedures are connected to critical thinking and argumentation. Describing the
scientific method in depth and the possible variations is far beyond the scope of this
chapter, so you may notice some discrepancies with specific scientific procedures you are
aware of. Physicists do their work differently than psychologist, who do their work
differently from astronomers, who do their work differently than anthropologists, who do
their work differently than chemists, who do their work differently than sociologists, etc.
The basic principles and methods are shared by different disciplines, but the specifics
vary. As you read the following keep in mind that it is an overview of the scientific
method, and it would take several classes for you to be exposed to all the complexities.
To start, I’ll describe ten principles that are the foundation of the scientific
method. Then I’ll describe the basic procedures of both descriptive and experimental
research. Finally, I’ll explain the difference between scientific hypotheses and theory.
PRINCIPLES OF THE SCIENFIC METHOD
The scientific method is designed to overcome common problems in reasoning by
devising procedures to account for them. The basis of those procedures can be summed
up by the following ten principles. The principles are not listed in any particular order;
they are all equally important.
Principle #1: Objectivity. As we go through our everyday lives we think we
encounter the world the way it is. However, the way we perceive the world is influenced
by our expectations of what we will experience, our biases, wishful thinking, our
individual and cultural beliefs, our states of mind, what we’re paying attention to at the
time, the language we and others use, and a variety of other factors. All of those
influences can cause anyone to perceive the world in an individual or subjective way that
does not correspond to what is actually going on. It doesn’t matter if a person is highly
intelligent, very honest, and has the best intentions. He or she can still be swayed by his
or her subjective perceptions.
The principle of objectivity means that the scientific method attempts to
overcome biases so different people who encounter the same phenomenon will report the
same experience and draw the same conclusion. If they follow the proper procedures
they can avoid being swayed by their own subjectivity. They describe what they did and
what they observed in the neutral language of reports rather than judgements. The
criteria for what “counts” as an incident of a particular phenomenon is clearly defined
ahead of the observations so different observers will all note it. Methods of recording
phenomena are devised so there is no question whether something happened or not.
You may have already heard the idea that objectivity is impossible to achieve
because people cannot eliminate their own subjectivity. While that is true it doesn’t
mean that steps cannot be taken to be more objective and minimize the effects of
For instance, if medical researchers want to determine if a new medicine is a
better treatment for heart disease than the treatment that is most commonly used, some of
them may want to believe in one treatment or the other. If they tried out the new
treatment they could probably come up with reasons why one is better using a priori
reasoning and making subjective judgments. If they follow the scientific method, though,
they create procedures to make sure their study isn’t biased toward one treatment or the
other. They determine ahead of time what criteria will be used to decide on the quality of
the treatments. They might decide that the best treatment is the one that reduces the
average blood cholesterol of the people in the study the most, as measured in a particular
way. At the end of the study anyone, regardless of their biases, can determine which
treatment best met the criteria. They may not reach the conclusion they hoped for, but
they’re more likely to reach the conclusion that is closest to the truth.
Notice that what they are doing here is following the stock issues for a proposition
of fact. They define what they mean, they establish criteria they will use to determine the
best treatment, making sure that their criteria could be applied to any treatment, not just
the one they already favor. Then they apply the criteria by discovering if one treatment
meets the criteria more than another one does.
Principle #2: Observation. The principle of observation means that scientists
do the best they can to actually examine the phenomenon they’re studying so the
conclusions they draw are based on more than speculation. Rather than decide what the
conclusion must be based on what they already know, they try to determine what is by
doing observations. Sometimes this is referred to as gathering empirical evidence,
because empirical means observable.
When you think of observation you may think of looking at something, and some
scientific endeavors do involve sight. But sight is not the only method of observing.
Observations may be done regarding sound, touch, smell, and taste. They may also be
done using instruments that extend and replace human senses.
Sometimes direct observation is impossible. The phenomenon under
investigation may be something that is either too difficult to observe directly or may be
something that cannot really be directly observed. For instance, in the social sciences
human attitudes are often studied, but an attitude cannot be directly observed. So
researchers have to observe behaviors associated with attitudes. The associated behaviors
are signs of the attitude, but they aren’t the attitude itself. When the phenomenon cannot
be directly observed the question arises whether the signs are really accurate indicators of
Sometimes you’ll need to make decisions under circumstances when you cannot
make observations, and you’ll have to do the best you can. However, when the
opportunity presents itself, you can have more faith in your conclusions if you gather
Principle #3: Measurement. When observing a phenomenon it becomes
important to accurately measure it, especially if comparisons are going to be made. You
can’t, for example, really tell if the size of something has changed unless you know how
big it was to begin with. And you can’t tell how much it has changed unless you can
accurately measure it. Some things are simple to measure and some are very difficult,
but most scientific investigations involve some kind of measurement. In our everyday
life it may be enough to say something looks like it got bigger, but scientific endeavors
attempt to be more precise, so great care is taken to measure well.
Principle #4: Controlling variables. Almost any event you can think of could
be affected by a variety of different factors. How well you feel on a particular can be
influenced by how much sleep you got the night before, what you ate and drank the
previous day, if you have a cold or not, the kind of exercise you did the previous day,
whether you’ve been under psychological stress, etc. If you wanted to reach a conclusion
about why you feel the way you should consider all the things that could affect your
physical state, not just the most obvious.
The same is true of answering scientific questions. A scientist may have an idea
of the way one event affects another, but if there are extraneous factors involved she can’t
be sure which one makes the difference. So she attempts to control the variables, either
by eliminating their influence or by making sure they influence everything being studied
Controlling variables aids in doing causal reasoning about whatever is studied
using the scientific method. Alternative potential causes are accounted for and the
chances of arguing for a false cause are reduced.
Principle #5: Replication. If what was found by one researcher is really true
other researchers ought to be able to reproduce those findings. That’s the idea behind the
principle of replication in the scientific method. Experiments and descriptive studies
should be explained in sufficient detail that others could do the same study over and see if
the get the same results. The more times the same results are found the more confidence
there can be that they are correct. Replication is repeating the procedures to see if they
consistently lead to the same results.
Replication of studies creates multiple examples, so reasoning by example can be
more sound. It also provides corroborating evidence so the facts can be used to make
more cogent arguments.
Principle #6: Generalization. When scientists generalize they draw conclusions
about members of a group who are not observed based on what is observed about some
members of the population. Usually, we cannot observe all the members of the group
because there are too many of them and studying all of them would be too costly both in
terms of time and money.
To make generalizations scientists make efforts to make sure that the sample,
which consists of the members of the group who are studied, is adequate. Remember that
generalization is done by reasoning by example, and each member of the sample is one
example of the larger population to which the generalization will be made. So the
standards for reasoning by example apply here. The sample has to be reasonably large
enough to make the generalization. Statisticians have determined how many members of
a large population need to be studied to draw a reasonably accurate conclusion. For very
large populations the number in the sample may be a lot smaller than you might think,
because at a certain point as you increase the sample size the increase in accuracy is so
small that increasing the size isn’t worth the benefit.
To make generalizations the sample that is studied also needs to be representative
of the larger population. That means all the segments of a the population are represented.
In some cases the researchers may select the members of the sample to be sure that all
types of members of the population are included. Another way to achieve a
representative sample is to choose it randomly, which means that every member of the
larger population has an equal chance of being selected for the sample. If the sample size
is large enough and the selection is truly random then the chances are very good that the
sample will be representative.
Finally, generalizations can be made with more confidence if the study is
repeated, either by the same researcher or by others. The repetition may be done by
repeating exactly the same procedures, or by studying the same phenomenon using
different methods. If the same results are found by different studies the researchers can
be more certain that their conclusions are correct and apply to the entire population. On
the other hand, if the results are not consistent then there is doubt that the outcome
applies to the entire population, and more study is needed.
Principle #7: Sharing findings. In general, the scientific method values the
sharing of findings of studies. That means that researchers communicate what was done
and the results with others, usually by publishing their studies in journals and by
presenting their studies at conferences. Sharing findings of studies is important for three
primary reasons. First, so they can identify unrecognized errors in their methods, in their
analysis, and in the conclusions they come to. When the findings are widely distributed
many other experts can look at what was done and notice if there were errors. The people
who did the study, and who want it to be successful, may inadvertently overlook errors
that others who are not as involved may catch. On the other hand, if no errors are noted
there can be confidence in the findings.
Second, sharing findings allows the study to be repeated and the results confirmed
by others. If the results of the study are not shared then nobody but the researchers know
what was found and the conclusions cannot be used by others. If the results are shared,
but not the methods, then no one can know if they should really accept the conclusions.
The third reason for sharing findings is simply to add to the body of knowledge
about the subject. Researchers are usually interested in advancing knowledge and they
know that the body of knowledge is not enlarged unless they and others are willing to
share what they’ve done and the results.
There are some cases when research is not shared, though. When businesses do
research for the purpose of improving their products or services they may not want to
share the findings because they would lose the competitive advantage they sought by
doing the research.
Principle #8: Peer Review. Peer review involves letting others who are
knowledgeable about the subject and research methods review the study to make sure it
was done correctly and analyzed correctly. Studies that go through peer review are
generally considered better than those that have not been reviewed.
The process of doing peer review usually happens prior to the wide distribution of
the study. Well respected journals use the process of peer review to decide if a study
should be published or not, and may reject more than ninety percent of the studies
submitted to them. Peer review is a method to both determine if a particular study was
properly done and to make sure that only the best studies are published. Studies that are
published in sources that are not peer reviewed are not regarded as highly as those that
Research projects often go through peer review at two different stages. The first
stage is prior to doing the research. Universities and laboratories funded by the
government have committees that are supposed to look at the proposed study and approve
it before it is done. The primary purpose of that examination is to make sure no humans
or animals are mistreated or endangered by the study, but they usually will also comment
on how appropriate the procedures are. Many private institutions have similar review
boards. The second stage of peer review is when the findings are published. The
researchers write reports and send them to journal editors. Those editors send copies to
experts in the field to review, usually without identifying who did the research so that
doesn’t bias the reviewers. The reviewers send their comments to the editor supporting
publication, supporting publication if there are changes made, or recommending
rejection. One of the prime reasons for rejecting a report is that the proper procedures
weren’t followed. So the peer review helps to weed out those studies that weren’t done
well enough to draw sound conclusions.
Principle #9: Falsification. This principle means that a hypothesis that cannot
be proven false cannot be studied using scientific methods. A hypothesis is a statement
of what the expected results of the study will be. If the subject being studied is such that
the hypothesis cannot be proven to be untrue then it is not something that can be studied
by the scientific method.
A hypothesis is a proposition of fact, and the study is the means by which the
proposition is supported or rejected. If it is a proposition that cannot be proven to be
untrue then it can’t be studied.
One type of hypothesis that cannot be falsified is one that proposes something
does not exist. The reason it cannot be falsified is because no matter what evidence you
have for its nonexistence, you can always say the researcher just didn’t look in the right
place. Another hypothesis that cannot be falsified is one that says something does exist,
but we can’t prove it because we don’t have the means to prove its existence.
Principle #10: Provisional Conclusions. Conclusions drawn from studies are
never the final word on the subject. They can always be altered or proven incorrect by
further studies. When you read about studies it may seem as if they say the findings are
absolutely true and cannot be doubted, but they really are saying what that study found
and how it fits with other knowledge about the subject.
PROCEDURES OF THE SCIENTIFIC METHOD
Studies done using the scientific method generally follow a common set of
procedures. Every study will not use every step in the following description, and some
disciplines commonly use variations of the basic procedure. Knowing the following
procedures can both help you think critically about studies you read about and design
your own studies so they can better stand up to critical scrutiny. If your field of study or
occupation call for you to use the scientific method you will learn far more about
scientific procedures than can be described here. The following description is also a
simplified version of what is really done; actual scientific studies are usually much more
complicated. However, if you are not in a scientific field you may still find yourself
making decisions that would be better made if you are familiar with scientific thinking
Scientific studies begin with a problem statement, which is a general statement
of what the researcher wants to find out. The problem statement helps the researcher
focus attention and make sure that everything done later is designed to fit the problem
statement. A problem statement might be something like, “I want to find a way to cure
From the problem statement comes a research question, which is a specific
question that the research is intended to answer. It might be something like, “Does
xidium reduce the effects of heart disease?” (By the way, “xidium” is just a word I made
up for an imaginary drug.) The specific research question is important, because
everything else in the research should be done to answer that specific question rather than
a more general question or a question similar to the research question. For instance,
“Does xidium have any health benefits?” is a much broader and much more vague
The study that is actually done may be either a descriptive study or an
experimental study. A descriptive study is designed to report on what “is” without
attempting to draw causal conclusions. An experimental study is a study designed to
draw a causal conclusion about how one variable affects another. The study in our
example would be an experimental study if the researchers wanted to find out if giving
heart patients a drug would somehow reduce the effects of heart disease. It would be a
descriptive study if they wanted to find out what portion of the general population has
heart disease, and the percentage of heart disease in different age groups.
Based on the research question that is asked and everything the researcher already
knows about the subject the researcher then devises a hypothesis, which is a prediction
of what the researcher expects to find. In everyday life we regularly make vague
predictions without establishing the problem statement or research question. In a more
rigorous scientific procedure you would more carefully state you hypothesis to account
for the variables and exactly what is studied. In our example it might be something like,
“Patients in the sample who are administered xidium will have a lower mortality rate than
those who administered a placebo.”
There are two types of variables that are involved in the hypothesis. One is called
the independent variable. The independent variable is what the researchers have control
over and predict to be the cause of a particular effect. The dependent variable is what is
expected to be affected by the independent variable. They’re called variables because
each can vary in some way, even if it is as simple as existing or not existing. In our
example, the administration of xidium would be the independent variable and the
dependent variable is the mortality rate. The researchers can control who gets xidium,
when they get it, and how much they get. They cannot control who dies from heart
disease. They predict they can influence who dies from heart disease, and decrease the
number of deaths among those who get xidium, but within the confines of the experiment
they cannot control mortality rates.
One of the first things a researcher doing a study will do is identify the population
he or she will study. The population is the entire group to which the study is intended to
apply. It may be everyone in the United States, women over the age of 45, redwood trees
within fifty miles of the California coast, television sets sold in the United States, or any
number of other groups that could be studied. In many cases when researchers want to
draw a conclusion about a group it would be too expensive and difficult to study all the
members of the group, so they study a sample. The sample consists of members of the
larger population that are actually studied. The researchers try to make sure they get a
sample that is of adequate size and that represents the population as a whole. In the heart
research example, the population may be “all Americans over the age of forty who have
arteriosclerosis.” The sample might be, “Two thousand randomly selected Americans
who have been diagnosed with arteriosclerosis.”
When designing the study the researchers also have to figure out how to measure
whatever they are studying. Measurement is simply the transformation of observations
into numbers to allow for statistical analysis. One way to do that is to actually count the
phenomenon, whether it’s counting the number of times something happens, counting
how long something is, counting how heavy something is, or various other ways of
counting. Another way is to turn something into a numerical form. For example,
someone’s attitude may be measured by a survey that allows for answers such as
“Strongly Agree,” and “Disagree.” The answer “Strongly Agree” may be counted as a
value of 5 while “Disagree” may be counted as 2. Turning non-numerical concepts into
numbers allows statistical analysis that wouldn’t be possible otherwise.
In deciding what kind of measurements to use researchers have to be concerned
with two different ideas: reliability and validity. Reliability has to do with the ability of
the measurement device to consistently give the same results when measuring the same
phenomenon. For instance, a scale is said to be reliable if, whenever the same item
placed on it the scale indicates that item weighs the same. If the measurement device is
unreliable the conclusion of the study can’t be as confident. Validity is the ability of the
measurement device to actually measure what it is supposed to measure. A scale, for
instance, would be an appropriate device for measuring weight but not for distance.
At this point the general procedures are different for descriptive studies and for
experimental studies. So first I’ll explain what is done in the design of descriptive
DESCRIPTIVE DESIGN The design of descriptive research is generally simple
than that for experimental research. Procedures are worked out to make the observations
and repeat them often enough that a generalization can be made. That doesn’t mean
descriptive research is necessarily easy, though. If surveys are used they have to be
designed in a way that the questions are not likely to be interpreted in multiple ways, do
not identify a “desired” answer, do not ask multiple questions, and accounts for other
concerns. Physical observations have to be done in ways that account for potentially
different perspectives and biases.
A typical descriptive study generally does the following:
1. Identify the population
2. Select the sample
3. Identify or devise a reliable and valid measurement instrument.
4. Gather data by using the measurement instrument to collect the measurements
you’re interested in.
5. Analyze the data statistically.
6. Draw conclusions.
EXPERIMENTAL DESIGN The design for experiments is more complicated
than for descriptive studies because the researcher is manipulating variables to find out
what would happen if certain changes are made.
As with descriptive studies the design begins by identifying the population and
the sample. The sample is then divided into two or more groups. One group is the
treatment group (or experimental group) and the other is the control group. In a relatively
simple experiment there will be one treatment group and one control group. In a more
complex experiment there will be multiple experimental groups.
The treatment group consists of the members of the sample who are exposed to
the experimental treatment. Remember that the experimental treatment is the
administration of the independent variable. That means whatever cause (independent
variable) the researcher hypothesizes will create an effect (change in the dependent
variable) is done to the treatment group. In our ongoing example, since the hypothesis is
that patients in the sample who are administered xidium will have a lower mortality rate
than those who administered a placebo, the treatment group is those who are administered
The control group consists of the members of the sample who are exposed to all
the same conditions as the treatment group except for the experimental treatment. If, for
instance, researchers want to know how well a fertilizer improves the growth of grass
they will set up at least two plots of grass. One plot will be fertilized and the other won’t.
They’ll make sure both plots have the same soil, the same amount of light, the same
amount of water, the same temperatures, etc. so the only difference in growth rates will
be due to the fertilizer. When working with humans it is more difficult to control all the
variables, but researchers do the best they can. In our example the assumption may be
that by choosing a large enough random sample, and by randomly assigning participants
to the treatment and control groups, that the overall experiences will be the same among
patients. The experimental group is given xidium and the control group is given a
placebo. A placebo is something that the control group is given that is similar to the
independent variable but has no known effect on the dependent variable. It is used
because just doing something that the patient thinks will help sometimes does help, and
the research should control for that. So, if xidium is administered in the form of a pill
taken three times a day, the patients in the control group would be take a sugar pill three
times a day.
Many experiments use a pre-test, treatment, post-test design. The pre-test
measures the dependent variable in the entire sample prior to any treatment being done.
The post-test measures the dependent variable in the entire sample after the treatment is
done. If the post-test shows there is more change in the treatment group than in the
control group, and if everything else is done correctly, then it is reasonable to conclude
that the independent variable caused the difference in the change. If there is no
difference in the change between the two groups then you would have to conclude that
the independent variable had no real effect.
In our example, the pre- and post-tests are pretty simple. In the pre-test everyone
is alive. The post-test is how many patients died in each group during the course of the
experiment. Real experiments are likely to be much more sophisticated, though, and
would measure the effect on other symptoms of heart disease as well. So in a real
experiment all the subjects might be given a complete physical with blood tests and a
stress test as the pre-test and again as the post-test. The researchers would determine the
change in a variety of variables as measured by the tests.
When the data are collected statistical analysis is done and conclusions are drawn
based on the results of the experiment. If the data show there is more change in the
treatment group than in the control group, and that the change can be shown statistically
to be unlikely to be due to chance, the hypothesis is confirmed.
HYPOTHESIS vs. THEORY
Among people who are not scientists there is often some confusion about the
difference between a hypothesis and a theory. We often hear people who don’t want to
accept a scientific theory say something like, “Oh, that’s just a theory,” as if that is proof
that the idea shouldn’t be taken seriously.
A scientific theory is an explanation of a phenomenon and a prediction of what
will happen in the future, based on the accumulation of a great deal of well collected data.
Scientific theories, especially those that are accepted in the scientific community, are not
just speculation. They have a great deal of evidence supporting them. Hypotheses, on
the other hand, are speculations of how one variable will affect another based on what is
known and before an experiment is conducted. When people say “Oh, that’s just a
theory” they are likely to be thinking of a theory as if it has no more support than a
Theories are accepted because they provide a cogent explanation for what
happens. They don’t just say one variable affects another, but they say how and why that
variable has the effect it does. They are also accepted because they accurately predict
how one variable will affect another. If there’s a reasonable explanation but the
predictions are inaccurate the theory is rejected. If there are competing theories they are
tested with more experiments to identify the strengths and weaknesses of each. The best
one is accepted, or both are rejected and another theory is proposed. Whichever theory is
accepted is subject to more research which may strengthen it or cast doubt on it.
It is true that theories come and go, but that happens because a better theory
supplants earlier theory. New ways of making measurements are devised, which
generates new data, which creates better understanding and exposes inaccuracies, and a
new theory to developed and tested to account for the new information. The experiments
and theorizing are shared with others and go through peer reviews to expose weaknesses.
The theories are revised and refined until they appear to make the best explanations and
So if you hear something presented as an accepted scientific theory, and if you
can trust the person presenting it, you can be pretty sure it has received a great deal of
scrutiny by people who are very good at examining the subject. And if you hear a theory
dismissed because it is just a theory, you should question if the person making the charge
knows what he or she is talking about.
OPPOSITION TO THE SCIENTIFIC METHOD
Some people really dislike the scientific method and reject it for all purposes.
Their reason is often because it doesn’t answer the kind of question they think are the
most important. There is some truth to that position, because the scientific method can
only answer questions of fact. Use of the method can help us to understand what “is” and
how one event affects another. It can’t answer questions of value or policy, though. The
scientific method can’t answer what is good or just, and it can’t tell us what to do with
the knowledge we gain. It’s unfair, though, to reject the scientific method entirely
because it doesn’t do what it’s not intended to do.
Another reason some people have for rejecting the scientific method is because
sometimes scientists don’t follow it very well. There have been highly publicized cases
where some scientists skipped some steps or outright lied about the data they collected.
That is reason to reject those studies and to be suspicious of anything else those scientists
produce, but it’s not a very sound reason to reject the method as a whole.
Sometimes people want to reject the scientific method because they find some
research to be unethical. There are examples of humans being harmed by unethical
scientific procedures and there are many people who find the use of animals in
experiments to be unethical. While there are reasons to advocate changing the way
specific experiments are done, that also is not a sound argument for dismissing science
Some people also are opposed to science and the scientific method because they
don’t like what is found. The results of research are contrary to some people’s beliefs or
provide evidence for policy changes to which they are opposed, so they reject science.
Sometimes there are reasonable arguments against a particular line of research because of
what will be done with it, but once again that doesn’t make a good argument against the
scientific method in general.
I’m not a scientist myself, but I can appreciate what scientists do and how they do
it. I do encounter opportunities to think about what scientists produce or use some
scientific findings in arguments almost every day. I find a basic understanding of how
the scientific method works to be very valuable to me as an ordinary person and as a
Objectivity: attempts to overcome biases so different people who encounter the same
phenomenon will report the same experience and draw the same conclusion.
Peer review: letting others who are knowledgeable about the subject and research
methods review the study to make sure it was done correctly and analyzed
Descriptive study: research designed to report on what “is” without attempting to draw
Experimental study: research designed to draw a causal conclusion about how one
variable affects another by controlling and manipulating variables.
Population: the entire group to which a study is intended to apply.
Sample: members of the larger population that are actually studied.
Reliability: the ability of the measurement device to consistently give the same results
when measuring the same phenomenon.
Validity: the ability of the measurement device to actually measure what it is supposed to
Treatment group: members of the sample who are exposed to the experimental
treatment. Also known as the experimental group.
Control group: the members of the sample who are exposed to all the same conditions
as the treatment group except for the experimental treatment.
Pre-test: measure of the dependent variable in the entire sample prior to any treatment
Post-test: measure of the dependent variable in the entire sample after the treatment is
Theory is an explanation of a phenomenon and a prediction of what will happen in the
future, based on the accumulation of a great deal of well collected data.
Hypothesis: a prediction of what the researcher expects to find based on what is already
known about the subject.
Independent variable: what the researchers have control over and predict to be the cause
of a particular effect.
Dependent variable: what the researchers expect to be affected by the independent