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Career Guide
Career developmentExperimental Research: Definition, Types and Examples
Experimental Research: Definition, Types and Examples
Updated August 16, 2024
Experimentation is a useful form of analysis that professionals use in a variety of industries.
Experimental research is a method of gathering information and data on a subject through observation
in controlled settings Understanding the benefits of experimental research design can help you better
use it in your professional career.
In this article, we define experimental research, discuss the types of experimental research design,
explore the advantages of using this research method and share example scenarios.
What is experimental research?
Experimental research is a form of comparative analysis in which you study two or more variables and
observe a group under a certain condition or groups experiencing different conditions. By assessing the
results of this type of study, you can determine correlations between the variables applied and their
effects on each group. Experimental research uses the scientific method to find preferable ways of
accomplishing a task for providing a service.
Related: Types of Research: Definitions and Examples
Types of experimental research design
A scientific researcher looks through a microscope while another person makes notes in the foreground.
Both are dressed in white coats.
There are three different types of experimental research design, divided by key elements related to how
you conduct each experiment. Within these types, there are also subdivisions that the behaviors within
the experiment can affect. The three main types of experimental research design are:
1. Pre-experimental research
A pre-experimental research study is an observational approach to performing an experiment. It’s the
most basic style of experimental research. Free experimental research can occur in one of these design
structures:
One-shot case study research design: In this form of experimental research, experimenters subject a
single group to a stimulus and test them at the end of the application. This allows researchers to gather
results for performance by individuals or entities subject to the stimuli being tested.
One-group pretest-posttest design: In this type of research, researchers apply a test both before and
after the application of the stimuli. This provides a comparison of performance with and without
application for researchers to make judgments about the effects of the stimuli on the subjects.
Static group comparison design: In a static group comparison, researchers assess two different groups,
with only one group receiving the stimuli the researchers are assessing. Testing occurs at the end of the
process, allowing the researchers to compare the results from the subjects who received the stimuli
against those who didn’t.
Related: Evidence-Based vs. Research-Based Programs: Definitions and Differences
2. Quasi-experimental research
Quasi-experimental research is similar to true experimental research, and experimenters can apply it in
similar ways. The primary distinction between the two is a lack of randomization when assigning
participants to groups in a quasi-experimental study. This usually occurs because of rules or regulations
that prevent researchers from applying random allocations in some settings, such as a research study at
a university.
Related: Research Design: What It Is (Plus 20 Types)
3. True experimental research
True experimental research is the main method of applying untested research to a subject. Under true
experimental conditions, participants receive randomized assignments to different groups in the study.
This removes any potential for bias in creating study groups to provide more reliable results. There are a
few design structures a researcher may use when performing experimental research, which differ based
on the number and style of groups used:
Posttest-only control group design
In this design structure, a researcher divides participants into two groups at random. One group acts as a
control and doesn’t receive the stimuli being tested, while the second group does receive the stimuli
researchers are assessing. Researchers perform tests at the end of the experiment to determine the
practical results of being exposed to the stimuli.
Related: What Is a Control in an Experiment? (With Definition and Guide)
Pretest-posttest control group design
Under this structure, researchers provide tests to the participants both before and after the non-control
group receives exposure to the stimuli. Researchers test groups twice, so this structure provides
multiple methods of assessing the results.
Experimenters can examine changes in performance for the non-control group, and they may also
determine if any changes occur due to participants undergoing the same test twice. They may do this by
checking if the control group has also changed, which researchers can then use to make adjustments as
needed when analyzing the data.
Related: What Is a Control Group? Definition and Examples
Solomon four-group design
This is the most comprehensive design structure for an experimental research project. Under the
Solomon four-group design, participants receive an assignment to one of four randomly allocated
groups. These groups provide all four possible permutations for both control and non-control groups
and post-test or pre- and post-test control groups. Having a comprehensive set of data with multiple
ways of differentiating between groups can enhance researchers’ abilities to reach conclusions based on
the resulting data.
Advantages of using experimental research
Experimental research provides you with more information when making professional decisions, which
might allow you to complete better and more profitable actions. There are many advantages of using
the experimental research approach, including:
Strong variable control
Experimental research occurs within a controlled setting. This provides you with significant influence
over the variables associated with the experiment you conduct. It allows you to tailor and experiment to
best match your needs, which can help you gain results that are applicable to your professional goals.
Related: 10 Types of Variables in Research and Statistics
Broad application across fields
Experimental research provides significant control, and it’s adaptable across a variety of professional
fields. This makes it an effective tool for professionals in all industries to understand. By adapting
experimental research to match your professional field, you can use it to gain key information that might
give you an advantage over your competitors.
Specific results
When conducting experimental research, your control allows you to specify the type of results your
research yields. If you know what information you’re trying to gather, you can devise an experiment that
isolates that data to provide the precise results needed. This makes experimental research an efficient
method of gaining information on a topic.
Actionable results
Experimental research provides results on which you can draw conclusions and act. It’s an effective
method when seeking to change behaviors or policies in your professional career. Many experiments
yield results that show a clear preference for the most effective option based on the variable of the
experimental studies. By applying the more effective method revealed, you can benefit from completing
the experiment.
Related: 7 Types of Experiments and What They Measure
Early identification of market trends
Following market trends is important for remaining competitive in a professional sector. You can use
experimental research to identify cause-and-effect relationships within markets. This can help you
determine what indicators represent an impending change in the market.
Accurately predicting how trends may shift can provide a significant professional advantage, as it allows
you to use the new conditions to maximize your benefits quickly. When used to identify a developing
market, for instance, acting early might allow you to claim a larger share of the market, giving you a
potential advantage in the future.
Related: What Is Experiment Marketing? (With Tips and Examples)
Foundational use in further experimentation
Experimental research is a foundational part of many types of analysis. The stronger understanding you
have of experimental research and its application, the more capable you may become of using it within
other frameworks and types of analysis. This can also help increase the effectiveness of your other
research and data analysis.
Related: Designing an Experiment: 8 Steps Plus Experimental Design Types
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Experimental research examples
Experimental research has broad usage and can provide meaningful information to professionals in
nearly any field. For instance, a researcher may use experimental research to gather valuable insight
that can steer a company’s performance and make it more productive or profitable. Here are some
example scenarios involving experimental research:
Advertisements example
A company seeking to market a new product opts to run two different versions of advertisements as
part of a marketing campaign. Using digital advertising through social media networks and advertising
platforms allows the company to view detailed breakdowns of ad performance. This allows for the quick
assessment of different options to optimize the company’s marketing plan.
The company tracks the performance of both advertisements to determine which is more effective.
After multiple rounds of testing, the company determines that one advertisement receives more
engagement and leads to more purchases than the other. The company then transfers the marketing
budget to the better advertisement option.
Demographics example
A company wants to use experimental research to identify the right demographic for its new service.
The company gathers different groups of consumers based on age, location and other factors.
Researchers then examine which groups produce the best results when exposed to the advertising
campaign for the service. This helps the company adjust the focus of both its current and future
marketing plans.
Product design example
A company is in the product development phase of introducing a new product to the market. When
designing the product, researchers use experimental methods to produce multiple prototypes and
conduct experiments to test the performance and capabilities of each design. These experiments help
the researchers find the most effective product design for the company.
The company also uses experimental research in the form of market testing with multiple designs of the
product. By allowing sample groups to experience the different product designs, the researchers can
assess which option presents the highest appeal to prospective customers. This helps the company
influence its development to best meet the existing market.
Solutions example
A company employs experimental research when working to develop new solutions to an existing
problem. The experiment allows the company to compare the results of different proposed solutions
and identify the most effective method of solving the problem. The company can then move forward
with its newly optimized behavior patterns.
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Career Guide
Career developmentDesigning an Experiment: 8 Steps Plus Experimental Design Types
Designing an Experiment: 8 Steps Plus Experimental Design Types
Updated August 16, 2024
Companies often need to conduct experiments to test new products and try new practices. These
experiments can help improve a company’s products and services and provide valuable research results.
To better understand how companies use this research method, it can be helpful to know how to design
an experiment.
In this article, we will define experiments, types of experimental design and share the steps you may
need to take when designing an experiment.
What is an experiment?
An experiment is a process that manipulates variables in order to draw conclusions and test a
hypothesis. This research method can be a hands-on way to test products and software and to create
effective business practices. For these experiments, research professionals usually use focus groups to
help reach a conclusion about a certain research topic.
Experiments can have several purposes. Commonly, professionals design experiments to compare two
business practices or components in a product, to find ways to ensure consistent production results and
to establish the most effective production methods.
Related: How To Become a Quality Assurance Tester
Types of experimental design
Research professionals often use one of three types of experimental design methods. Researchers
usually separate these types by comparing aspects of control groups, such as their size or sorting
method. Here’s an explanation of those designs:
Independent measures
Independent measures use different participants to be in different test groups. This means the
professionals who supervises the experiment separates participants into two or more groups and treat
each group differently. However, each participant is only used to test one variable, and the researchers
sort these participants randomly into the focus groups.
Example: If a bakery wanted to improve its chocolate chip cookie recipe, the bakers may use an
independent measures design type to decide which recipe upgrade may be best. So in one test group,
they may ask the participants to eat a cookie that has more sugar in it. The second group may eat a
cookie with an unchanged recipe to act as the control.
In this scenario, the bakery would ensure each participant only ate the cookie the bakery assigned to
their test group instead of each participant eating both the variable cookie and the control cookie.
Repeated measures
Repeated measures use the same participants throughout the experiment. This means the control test
group and variable groups consist of the same participants, but the researchers test them at different
times. Repeated measures experiments can save time by using the same participants throughout the
study. It also requires fewer people to take part in the experiment.
Example: The participants first eat the control cookie, which would be the original recipe, and then later
eat the variable cookie, which the bakers made with a different recipe.
Matched pairs
When practicing an experiment designed with matched pairs, the professionals who are conducting the
experiment assign each participant to another, making a matched pair. This can allow researchers to test
how their product or practice may appeal to different demographics and notice any trends in participant
responses. To do this, the professionals may interview each participant and make a note of those with
similar values, or they may match participants based on their demographics.
Example: After all the participants receive a match, the researchers separate the pairs into opposing
groups. For example, the bakery may match two women of a similar age and have one eat the original
recipe cookie and the other eat the new recipe cookie.
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How to design an experiment
To design your own experiment, consider following these steps and examples:
1. Determine your specific research question
To begin, craft a specific research question. A research question is a topic you are hoping to learn more
about. In order to create the best possible results, try to make your topic as specific as possible.
For example, in the bakery scenario, the bakers’ research question would be to test if adding extra sugar
could improve the taste of the cookie and therefore possibly increase business and customer
satisfaction.
2. Define the variables
In order to keep your experiment accurate and organized, it can be helpful to define the variables
involved in your experiment. There are three variables you may need to address:
Independent: The independent variable is the aspect of the experiment that changes. In the example,
the independent variable is the amount of sugar in the cookie.
Dependent: The dependent variable is the aspect of the experiment that changes because of the
independent variable. In the example, the dependent variable is the taste of the cookie.
Control: The control of your experiment is an aspect that stays the same. This is used to help researchers
contextualize the results of the experiment. In the example, the control is the cookie made with the
original recipes.
3. Form a hypothesis
A hypothesis is the expected outcome of the experiment. Professionals record their hypotheses to
measure the success of their experiment. In business-related experiments, a professional’s hypothesis
often closely aligns with the research question.
For example, the hypothesis of the bakery’s experiment may be that increasing the amount of sugar in
its cookie can improve the taste. If they did not think adding more sugar to their recipe would improve
the cookie, they may study a different research question to save time and resources.
4. Choose a design type
The type of experimental design you chose for your experiment can affect how you conduct your
experiment. When deciding which design type to use, you may want to consider your available
resources, including the time you are able to commit to the experiment.
For example, if you would like to save time and effort, you may want to consider using repeated
measures, as it can take less time to assemble the test group.
5. Create a test group
Knowing what experiment design type you may use can help determine how you assemble your test
groups. When creating a test group, here are some aspects you may want to consider:
Experiment size: It’s important to ensure you have an even number of people in each group to take part
in your study. This is because equal test group sizes can ensure fair and accurate experiment results. For
example, if you have two test groups, you may want both to have 10 participants in them.
Group sorting: The design type you chose for your experiment can affect the way you sort your
participants into test groups. For example, if you chose to use independent measures, you most likely
can randomly assign the participants to test groups.
Target audience: When choosing participants for your experiment, consider your target audience to
ensure useful results. For example, if the bakery mostly catered to children, it would make sense to use
young participants in order to involve the target audience.
Read more: What Is a Control in an Experiment? Definition and How-To Guide
6. Collect research
Collecting research involves conducting your experiment and recording your observations. Document all
of your observations, even the ones you may feel are irrelevant. This can help provide plenty of data to
analyze later.
For example, while conducting their experiment, the bakery employees record the participants’
reactions and comments to the cookie they are tasting.
Related: 10 Types of Variables in Research and Statistics
7. Repeat the experiment
Repeating your experiment can be one of the most important steps to ensure that the data you
collected is accurate. This can account for any unknown manipulations in the experiment, such as a
small human error or the personal preferences of the participants.
For example, if the bakery unknowingly recruited many participants who did not like the taste of cookies
at all, these participants’ views on cookies could affect the result of the experiment and yield an
inaccurate conclusion. Repeating the experiment can help eliminate this.
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