| Biological
Communications (Biol 3920) |
THE SCIENTIFIC METHOD
A Protocol for Experimental Research
Investigations:
Recommended Approach*
A Recommended Approach to resolving Experimental
Research includes information taken from An
Approach to Experimental Research: Elementary Protocol. In addition
advanced concepts have been provided to help distinguish between different categories
of scientific
studies. Emphasis has been on how the Scientific Method may be exercised in
resolving experimental research,
and the different steps encountered.
Content:
| Introduction
| Research
Project | Experimental Errors |
| What If My Science Project Doesn't Work? |
Categories of the Scientific Method
A confusing aspect of science is that not all fields
of science arrive at conclusions in the same way. The physical sciences, i.e. physics,
chemistry, geology, use experimental forms of the "scientific
method." The physical sciences do experiments to gather numerical data from
which relationships are derived, and conclusions are drawn. The more descriptive
sciences, such as anthropology, botany, and zoology may use a form of the
scientific method that
involves gathering information by visual observation or interviewing.
However, experimental research in biology, including anthropology, botany, and zoology must
meet the same ridged constraints in exercising the scientific method as the
physical sciences, e.g. requiring a control and a treatment or test group for
comparison. What we find in common among all sciences is a requirement for
establishing an hypothesis to explain
observations, the gathering of data, and based on this data, the drawing of
conclusions that confirm or deny the original hypothesis, specifically the
rejection of the null hypothesis (which states that there are no statistically
significant differences between the control and treatment groups). The difference is in
what is considered data, and how data are gathered and processed.
Observations taken by a physical scientist are
numbers, typically referred to as "data." Data are often plotted as graphs and presented
formally in figure formats. Figures, such as regression slopes, may be used to derive equations that in
turn may be helpful in making predictions. Data, for an anthropologist, could be a
recorded interview. Interviews may be compared to other related information.
Hence the distinction between the exact sciences (physical sciences that use
numbers to measure and calculate results), and other sciences that use
descriptions and inferences to arrive at results.
The following information assumes you are
planning to carry-out an experimental research study that uses the scientific method to gather data and test
hypotheses.
Understanding the
Experimental Scientific Method
Steps listed below will be helpful in systematically
making observations in a research
investigate that can be tested following the protocols inherent in the
scientific method. Not
all questions can be resolved with by the experimental scientific method. You must
choose a question or problem that can be formulated in terms of hypotheses that
can be tested. Tests done to check hypotheses are by definition experiments. To design
a suitable experiment you must make an educated guess about the things or
variables that
affect the system you want to investigate. This
requires thought, information gathering, and a study of the available
"definitive" information relating to your problem. As you carry-out an
experiment, you will record data that
measures the effect of variables. Using these data you can make calculation to
generate results.
Results are presented in the form of tables and figures revealing trends related to how the variables affect the system you are working with.
Based on these trends, you can draw conclusions about the hypothesis you
originally stated.
Cause-and-Effect: the Cornerstone of the Experimental Scientific Method
The existence of "cause and effect
relationships" in nature is what makes experimental research possible.
Hypotheses can only be verified using the scientific method if
there is a cause and effect relationship between the variables you have chosen
and the system you are studying.
What
Good is Experimental Research?
Experimental research must exercise the scientific
method (hypotheses tests) in resolving cause
and effect relationships in nature. To establish the hypothesis statement one
must formulate an "educated" guess regarding what the
cause-and-effect relationship may be. Results generated by testing the
hypothesis provides conclusions allowing you to predict the
result of future cause-and-effect relationships. Once accomplished, you may be
in a position harness similar effects to help accomplish some need. Technology is the area that applies the findings
of the sciences to produce machines, or do work for us.
A protocol for exercising the scientific method in experimental
research usually includes these primary categories: Observation, Hypothesis, Controlled Experiment,
Conclusion. To actually carry-out or run an experimental research experiment,
additional components are required within each category. The
following protocol more accurately reflects the course of an actual experimental
investigation.
Initial Observation
You notice something, and wonder why it happens. You
see something and wonder what causes it. You want to know how or why something
works. You ask questions about what you have observed. You want to investigate.
The first step is to clearly write down exactly what you have observed.
Be Knowledgeable by Literature Searches, Information Gathering and Logical
Reasoning
Find out about what you want to investigate. In order
to be informed in the area of research you wish to pursue read scientific
peer-reviewed journal articles and discuss your ideas with professionals who are
knowledgeable. Keep track of where you acquired your information and what the
important results/conclusions were. Synthesize and integrate critical
information to become informed and knowledgeable in the subject so you can meet
the following requirements.
Title
Choose a title that describes the research you will be
investigating. A title should be an "integration" of specific words
what that specific and precisely that thoroughly addresses the research.
State the
Objective/Purpose of
the Proposed Research
What do you want to find out? Write a statement that
describes what research you want to do. Use your observations and questions
[education you have gained] to formulate and write the statement.
Identify
Test Variables
Based on your gathered information, make an educated
guess about what types of things affect the system you are working with.
Identifying variables is necessary before you can formulate a hypothesis.
Stating the Hypothesis
When you think you know what variables may be
involved, think about ways to change one at a time. If you change more than one
at a time, you will not know what variable is causing your observation.
Sometimes variables are linked and work together to cause something. At first,
try to choose variables that you think act independently of each other. At this
point, you are ready to translate your questions into hypothesis. A
hypothesis is a question you have reworded into a form that can be tested
by an experiment. Once you have identified the Hypothesis it must be
restated [Falsified] as a Null Hypothesis [stating that there will be NO
DIFFERENCE BETWEEN THE EXPERIMENTAL TREATMENT AND CONTROL GROUPS]. Note that the
treatment group is subjected to the variable you wish to consider. Once
the null hypothesis has been tested and the experiment is complete the results
should show that the experimental treatment had no effect on the outcome of the
investigation.
Make a list of your answers to the questions you
have. This can be a list of statements describing how or why you think the
observed things work. These questions must be framed in terms of the variables
you have identified. There is usually one hypothesis for each question you have.
You must do at least one experiment to test each hypothesis. This is a very
important step. If possible, ask a faculty in the biology department to go over
the hypothesis with
you.
Designing an Experiment to
Test Your Hypothesis
Design an experiment to test each hypothesis. Make a
step-by-step list of what you will do to answer each question. This list is
known as an experimental procedure [usually embedded in the Methods and
Materials section of the study]. For an experiment to give answers you can
trust, it must have a "control." A control is an additional
experimental trial or run. It is a separate experiment, done exactly like the
treatment [variable] experiment. So the only difference in the control group is that no experimental variables are changed. A
control is a neutral "reference point" for comparison that allows you
to see what changing a variable does by comparing it to not changing anything.
Control and treatment experiments are typically done at the same time. Dependable controls are sometimes very hard to develop. They can be the hardest
part of a project. Without a control you cannot be sure that changing the
variable causes your observations. A series of experiments that includes a
control is known as a "controlled experiment."
Experiments are often done many times to guarantee
that what you observe is reproducible, or to obtain an average result.
Reproducibility is a crucial requirement. Without reproducibility you cannot trust your
results. Reproducible experiments reduce the chance that you have made an
experimental error, or observed a random effect during one particular
experimental run.
Some Guidelines for Experimental Procedures
- Select only one variable to change in the
experiment.
- Change something that will help you test the
null hypothesis.
- The procedure must tell how you will change the
variable.
- The procedure must explain how you will measure
the degree of change.
- Each experiment needs a "control" for
comparison to a "treatment or test" group so you can measure, with
a degree of confidence, how significant the change actually is.
- A statement must be included that addresses the
statistical approach that is to be employed in processing the data.
Obtain Materials and
Equipment
Make a list of the equipment you need to carry-out the
experiments. If you need special equipment, check with the faculty. Another
source of science materials are mail order supply companies such [check with
instructor].
Carry-out the Experiments and
Record Data
Experiments are often done in series. A series of
experiments can be done by changing one variable a different amount each time in
the treatment group. A
series of experiments is made up of separate experimental "runs;" each
run has a control and a treatment group. During each run you make a measurement of how much the variable affected the
system under study. For each run, a different amount of change in the variable
is used. This produces a different amount of response in the system. You measure
this response, or record data, in a table for this purpose. This is considered
"raw data" since it has not been processed or interpreted yet. When
raw data gets processed mathematically [statistically], for example, it becomes results.
As you carry-out experiments, record all numerical
measurements made. Data can be amounts of chemicals used, how long something is,
the time something took, the weight, etc. If you are not making measurements, you
probably are not doing experimental research.
Record Your
Observations
Observations can be written descriptions of what you
noticed during an experiment, or problems encountered. Keep careful notes of
everything you do, and everything that happens. Observations are valuable when
drawing conclusions, and useful for locating experimental errors.
Data Processing and Calculations
Before doing any calculations of the raw data it
should be critiqued for data quality and acceptability. Once you have acceptable data it
may be processed to
obtain the numbers you need to complete the calculations and draw your conclusions. For example, you weighed a
container. This weight is recorded in your raw data table as "wt. of
container." You then added a substance to the container and weighed it again.
This would be entered as "wt. of container + substance." Once you are
confident the data are good, do the calculation to find out how much substance was used in
the
experimental run:
(wt. of container + substance) - (wt. of container) =
wt. of substance used
Each calculated answer may be entered on a
"data form" before transcribing it into a table in an
Appendix section; the calculated mean values may then be embedded in tables used in the Results section.
Not all experiments need a calculation section.
However, if you do not have calculations you may not be using the
experimental research method. If you have calculations to make, you probably
are using the experimental scientific method.
Summarize Results
Summarize and explain the results in written
statements of what occurred during the experiments. This can be in the form of a
table of processed numerical mean values and plotted in graphs to generate
figures. It could also be a written
statement of what occurred during experiments.
It is from calculations using recorded raw data that
tables and figures are made. Studying tables and figures, one may see trends that
tell how different variables cause the changes observed. Based on these trends,
one may draw conclusions about the system under study. These conclusions help confirm or
reject the original hypothesis. Often, mathematical equations can be derived from graphs.
Equations allow one to predict how a change will affect
the system without the need to do additional experiments. Advanced levels of
experimental research rely heavily on graphical and mathematical analysis of
data. At this level, science becomes even more interesting and powerful.
Draw Conclusions
Using the trends identified in the experimental data
and your experimental observations, try to answer your original questions. Is
your hypothesis correct? Did you disprove and reject the null hypothesis? Now is the time
to pull together what happened, and assess the experimental results you
achieved.
Additional
"Take-home" Messages in the Conclusion
- If your hypothesis is not correct, what could be
the answer to your question?
- Summarize difficulties or problems you
encountered in the experiment.
- Do you need to change the procedure and repeat
your experiment?
- What would you do different next time?
- Identify other important contributions
identified in the research [not always found in results].
Try to Answer Related
Questions
Knowledge you have gained may allow you to better answer other
questions. Many questions are related. Several new questions may have occurred
to you while doing experiments. You may now be able to understand or verify
concerns that you discovered while carrying-out the research investigation. Questions
tend to lead to additional questions, leading to more hypotheses that need to be
tested.
How Confident are You in the Results?
Should the results reveal no difference in the
end-points you measured in the control and treatments groups, the variable you changed may not affect the system
you are investigating. If you did not observe a consistent, reproducible trend
in your series of experimental runs there may be experimental errors affecting
your results. The first thing to check is how you are taking your measurements.
Is the measurement method questionable or unreliable? Possibly you are reading a
scale incorrectly, or maybe the measuring instrument is operating erratically.
Finding that experimental errors are
influencing your results, carefully rethink the design of the experiments.
Review each component of the procedure to isolate sources of potential errors.
Have a scientist or professional in the field review the experimental procedure
and approach used in processing the data. Sometimes the designer and operator of an experiment can miss the obvious.
Random Errors
Assuming your measurement method is not the cause, try to
identify if the source of error is systematic or random. Random errors are more obvious.
They result in non-reproducible data that doesn't make sense. In this case, runs
with the same combination of variables, and even the control itself, cannot be
duplicated. Some randomness is always present in nature. No two measurements are
exactly the same. You must judge if the differences in your data can be
explained by nature operating normally.
A random error may be occurring because you are
doing something differently in each run. For example, you are not careful in
cleaning your reaction vessels and some of the chemicals are being carried over
from the last experiment. Scientists use various statistical tests to determine
if the difference between runs is due to randomness in nature, or to the way
they are doing the experiments.
Systematic Errors
Systematic errors are harder to find. Your data and
results may look consistent and reproducible. Here you may be doing something
you are not aware of that is causing all your measurements to be off the same
amount. For example, if you were not aware that a digital meter had been
incorrectly calibrated and now starts at 2" instead of 1", all your measurements
would be one unit off. This is a systematic error because all your data are affected the same
degree, and in the same direction. One way to check for
systematic errors is to run experiments following a different design that should give
the same answers. Scientists often do different kinds of experiments to cross
check their results. Another way to locate errors is to have an independent
investigator repeat your experiments. Others should get the same results you
did.
Linked Variables
Your results can be invalid if your variables are not
independent of one another, and you have not noticed this. Variables are
independent if they produce their effects separately from each other. In other
words, changing one variable does not affect changes produced by another
variable.
No matter what happens, you will learn something.
Science is not only about getting "the answer." Even if your
experiments don't answer your questions, they will provide ideas that can be
used to design other experiments. Knowing that something didn't work, is
actually knowing quite a lot. Unsuccessful experiments are an important step in
finding an answer. Scientists who study extremely complex problems can spend a
lifetime and not find "the answer." Even so, their results are
valuable. Eventually, someone will use their work to find the answer. Are you
that person? [Statement
of Completion]
An
Approach to Experimental Research: Elementary Protocol
* Taken
from: "Experimental
Science Project"
David Morano, Assoc. Professor
Mankato State University
27 May 1995
dmorano@vax1.mankato.msus.edu
and edited and reformatted for use as
an example.