true experimental research sample thesis

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The effectiveness of family planning programs evaluated with true experimental designs.

OBJECTIVES: This paper describes the magnitude of effects for family planning programs evaluated with true experimental designs. METHODS: Studies that used true experimental designs to evaluate family planning programs were identified and their results subjected to meta-analysis. RESULTS: For the 14 studies with the information needed to calculate effect size, the Pearson r between program and effect variables ranged from -.08 to .09 and averaged .08. CONCLUSIONS: The programs evaluated in the studies considered have had, on average, smaller effects than many would assume and desire.

Full text is available as a scanned copy of the original print version. Get a printable copy (PDF file) of the complete article (1.0M), or click on a page image below to browse page by page. Links to PubMed are also available for Selected References .

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

• Fisher AA, Laing J, Stoeckel J. Guidelines for overcoming design problems in family planning operations research. Stud Fam Plann. 1985 Mar-Apr; 16 (2):100–105. [ PubMed ] [ Google Scholar ]
• Sherris JD, London KA, Moore SH, Pile JM, Watson WB. The impact of family planning programs on fertility. Popul Rep J. 1985 Jan-Feb;(29):J733–J771. [ PubMed ] [ Google Scholar ]
• Reynolds J. Evaluation of family planning program performance: a critical review. Demography. 1972 Feb; 9 (1):69–86. [ PubMed ] [ Google Scholar ]
• Foreit JR, Foreit KG. Quarterly versus monthly supervision of CBD family planning programs: an experimental study in northeast Brazil. Stud Fam Plann. 1984 May-Jun; 15 (3):112–120. [ PubMed ] [ Google Scholar ]
• Chan KC. Hong Kong: report of the IUD reassurance project. Stud Fam Plann. 1971 Nov; 2 (11):225–233. [ PubMed ] [ Google Scholar ]
• Phillips JF, Silayan-Go A, Pal-Montano A. An experiment with payment, quota, and clinic affiliation schemes for lay motivators in the Philippines. Stud Fam Plann. 1975 Sep; 6 (9):326–326. [ PubMed ] [ Google Scholar ]
• Rosenfield AG, Limcharoen C. Auxiliary midwife prescription of oral contraceptives. An experimental project in Thailand. Am J Obstet Gynecol. 1972 Dec 1; 114 (7):942–949. [ PubMed ] [ Google Scholar ]
• Bongaarts J. Population policy options in the developing world. Science. 1994 Feb 11; 263 (5148):771–776. [ PubMed ] [ Google Scholar ]

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True Experimental Design

True experimental design is regarded as the most accurate form of experimental research, in that it tries to prove or disprove a hypothesis mathematically, with statistical analysis.

This article is a part of the guide:

• Research Designs
• Quantitative and Qualitative Research
• Literature Review
• Quantitative Research Design

Browse Full Outline

• 1 Research Designs
• 2.1 Pilot Study
• 2.2 Quantitative Research Design
• 2.3 Qualitative Research Design
• 2.4 Quantitative and Qualitative Research
• 3.1 Case Study
• 3.2 Naturalistic Observation
• 3.3 Survey Research Design
• 3.4 Observational Study
• 4.1 Case-Control Study
• 4.2 Cohort Study
• 4.3 Longitudinal Study
• 4.4 Cross Sectional Study
• 4.5 Correlational Study
• 5.1 Field Experiments
• 5.2 Quasi-Experimental Design
• 5.3 Identical Twins Study
• 6.1 Experimental Design
• 6.2 True Experimental Design
• 6.3 Double Blind Experiment
• 6.4 Factorial Design
• 7.1 Literature Review
• 7.2 Systematic Reviews
• 7.3 Meta Analysis

For some of the physical sciences, such as physics, chemistry and geology, they are standard and commonly used. For social sciences, psychology and biology, they can be a little more difficult to set up.

For an experiment to be classed as a true experimental design, it must fit all of the following criteria.

• The sample groups must be assigned randomly .
• There must be a viable control group .
• Only one variable can be manipulated and tested. It is possible to test more than one, but such experiments and their statistical analysis tend to be cumbersome and difficult.
• The tested subjects must be randomly assigned to either control or experimental groups.

The results of a true experimental design can be statistically analyzed and so there can be little argument about the results .

It is also much easier for other researchers to replicate the experiment and validate the results.

For physical sciences working with mainly numerical data, it is much easier to manipulate one variable, so true experimental design usually gives a yes or no answer.

Disadvantages

Whilst perfect in principle, there are a number of problems with this type of design. Firstly, they can be almost too perfect, with the conditions being under complete control and not being representative of real world conditions.

For psychologists and behavioral biologists, for example, there can never be any guarantee that a human or living organism will exhibit ‘normal’ behavior under experimental conditions.

True experiments can be too accurate and it is very difficult to obtain a complete rejection or acceptance of a hypothesis because the standards of proof required are so difficult to reach.

True experiments are also difficult and expensive to set up. They can also be very impractical.

While for some fields, like physics, there are not as many variables so the design is easy, for social sciences and biological sciences, where variations are not so clearly defined it is much more difficult to exclude other factors that may be affecting the manipulated variable.

True experimental design is an integral part of science, usually acting as a final test of a hypothesis . Whilst they can be cumbersome and expensive to set up, literature reviews , qualitative research and descriptive research can serve as a good precursor to generate a testable hypothesis, saving time and money.

Whilst they can be a little artificial and restrictive, they are the only type of research that is accepted by all disciplines as statistically provable.

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Martyn Shuttleworth (Mar 24, 2008). True Experimental Design. Retrieved Apr 09, 2024 from Explorable.com: https://explorable.com/true-experimental-design

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Experimental Research Design — 6 mistakes you should never make!

Since school days’ students perform scientific experiments that provide results that define and prove the laws and theorems in science. These experiments are laid on a strong foundation of experimental research designs.

An experimental research design helps researchers execute their research objectives with more clarity and transparency.

In this article, we will not only discuss the key aspects of experimental research designs but also the issues to avoid and problems to resolve while designing your research study.

Table of Contents

What Is Experimental Research Design?

Experimental research design is a framework of protocols and procedures created to conduct experimental research with a scientific approach using two sets of variables. Herein, the first set of variables acts as a constant, used to measure the differences of the second set. The best example of experimental research methods is quantitative research .

Experimental research helps a researcher gather the necessary data for making better research decisions and determining the facts of a research study.

When Can a Researcher Conduct Experimental Research?

A researcher can conduct experimental research in the following situations —

• When time is an important factor in establishing a relationship between the cause and effect.
• When there is an invariable or never-changing behavior between the cause and effect.
• Finally, when the researcher wishes to understand the importance of the cause and effect.

Importance of Experimental Research Design

To publish significant results, choosing a quality research design forms the foundation to build the research study. Moreover, effective research design helps establish quality decision-making procedures, structures the research to lead to easier data analysis, and addresses the main research question. Therefore, it is essential to cater undivided attention and time to create an experimental research design before beginning the practical experiment.

By creating a research design, a researcher is also giving oneself time to organize the research, set up relevant boundaries for the study, and increase the reliability of the results. Through all these efforts, one could also avoid inconclusive results. If any part of the research design is flawed, it will reflect on the quality of the results derived.

Types of Experimental Research Designs

Based on the methods used to collect data in experimental studies, the experimental research designs are of three primary types:

1. Pre-experimental Research Design

A research study could conduct pre-experimental research design when a group or many groups are under observation after implementing factors of cause and effect of the research. The pre-experimental design will help researchers understand whether further investigation is necessary for the groups under observation.

Pre-experimental research is of three types —

• One-shot Case Study Research Design
• One-group Pretest-posttest Research Design
• Static-group Comparison

2. True Experimental Research Design

A true experimental research design relies on statistical analysis to prove or disprove a researcher’s hypothesis. It is one of the most accurate forms of research because it provides specific scientific evidence. Furthermore, out of all the types of experimental designs, only a true experimental design can establish a cause-effect relationship within a group. However, in a true experiment, a researcher must satisfy these three factors —

• There is a control group that is not subjected to changes and an experimental group that will experience the changed variables
• A variable that can be manipulated by the researcher
• Random distribution of the variables

This type of experimental research is commonly observed in the physical sciences.

3. Quasi-experimental Research Design

The word “Quasi” means similarity. A quasi-experimental design is similar to a true experimental design. However, the difference between the two is the assignment of the control group. In this research design, an independent variable is manipulated, but the participants of a group are not randomly assigned. This type of research design is used in field settings where random assignment is either irrelevant or not required.

The classification of the research subjects, conditions, or groups determines the type of research design to be used.

Advantages of Experimental Research

Experimental research allows you to test your idea in a controlled environment before taking the research to clinical trials. Moreover, it provides the best method to test your theory because of the following advantages:

• Researchers have firm control over variables to obtain results.
• The subject does not impact the effectiveness of experimental research. Anyone can implement it for research purposes.
• The results are specific.
• Post results analysis, research findings from the same dataset can be repurposed for similar research ideas.
• Researchers can identify the cause and effect of the hypothesis and further analyze this relationship to determine in-depth ideas.
• Experimental research makes an ideal starting point. The collected data could be used as a foundation to build new research ideas for further studies.

6 Mistakes to Avoid While Designing Your Research

There is no order to this list, and any one of these issues can seriously compromise the quality of your research. You could refer to the list as a checklist of what to avoid while designing your research.

1. Invalid Theoretical Framework

Usually, researchers miss out on checking if their hypothesis is logical to be tested. If your research design does not have basic assumptions or postulates, then it is fundamentally flawed and you need to rework on your research framework.

2. Inadequate Literature Study

Without a comprehensive research literature review , it is difficult to identify and fill the knowledge and information gaps. Furthermore, you need to clearly state how your research will contribute to the research field, either by adding value to the pertinent literature or challenging previous findings and assumptions.

3. Insufficient or Incorrect Statistical Analysis

Statistical results are one of the most trusted scientific evidence. The ultimate goal of a research experiment is to gain valid and sustainable evidence. Therefore, incorrect statistical analysis could affect the quality of any quantitative research.

4. Undefined Research Problem

This is one of the most basic aspects of research design. The research problem statement must be clear and to do that, you must set the framework for the development of research questions that address the core problems.

5. Research Limitations

Every study has some type of limitations . You should anticipate and incorporate those limitations into your conclusion, as well as the basic research design. Include a statement in your manuscript about any perceived limitations, and how you considered them while designing your experiment and drawing the conclusion.

6. Ethical Implications

The most important yet less talked about topic is the ethical issue. Your research design must include ways to minimize any risk for your participants and also address the research problem or question at hand. If you cannot manage the ethical norms along with your research study, your research objectives and validity could be questioned.

Experimental Research Design Example

In an experimental design, a researcher gathers plant samples and then randomly assigns half the samples to photosynthesize in sunlight and the other half to be kept in a dark box without sunlight, while controlling all the other variables (nutrients, water, soil, etc.)

By comparing their outcomes in biochemical tests, the researcher can confirm that the changes in the plants were due to the sunlight and not the other variables.

Experimental research is often the final form of a study conducted in the research process which is considered to provide conclusive and specific results. But it is not meant for every research. It involves a lot of resources, time, and money and is not easy to conduct, unless a foundation of research is built. Yet it is widely used in research institutes and commercial industries, for its most conclusive results in the scientific approach.

Have you worked on research designs? How was your experience creating an experimental design? What difficulties did you face? Do write to us or comment below and share your insights on experimental research designs!

Frequently Asked Questions

Randomization is important in an experimental research because it ensures unbiased results of the experiment. It also measures the cause-effect relationship on a particular group of interest.

Experimental research design lay the foundation of a research and structures the research to establish quality decision making process.

There are 3 types of experimental research designs. These are pre-experimental research design, true experimental research design, and quasi experimental research design.

The difference between an experimental and a quasi-experimental design are: 1. The assignment of the control group in quasi experimental research is non-random, unlike true experimental design, which is randomly assigned. 2. Experimental research group always has a control group; on the other hand, it may not be always present in quasi experimental research.

Experimental research establishes a cause-effect relationship by testing a theory or hypothesis using experimental groups or control variables. In contrast, descriptive research describes a study or a topic by defining the variables under it and answering the questions related to the same.

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13.2: True experimental design

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• Page ID 135156

• Matthew DeCarlo, Cory Cummings, & Kate Agnelli
• Open Social Work Education

Learning Objectives

Learners will be able to…

• Describe a true experimental design in social work research
• Understand the different types of true experimental designs
• Determine what kinds of research questions true experimental designs are suited for
• Discuss advantages and disadvantages of true experimental designs

True experimental design , often considered to be the “gold standard” in research designs, is thought of as one of the most rigorous of all research designs. In this design, one or more independent variables are manipulated by the researcher (as treatments), subjects are randomly assigned to different treatment levels (random assignment), and the results of the treatments on outcomes (dependent variables) are observed. The unique strength of experimental research is its  internal validity and its ability to establish ( causality ) through treatment manipulation, while controlling for the effects of extraneous variable. Sometimes the treatment level is no treatment, while other times it is simply a different treatment than that which we are trying to evaluate. For example, we might have a control group that is made up of people who will not receive any treatment for a particular condition. Or, a control group could consist of people who consent to treatment with DBT when we are testing the effectiveness of CBT.

As we discussed in the previous section, a true experiment has a  control group with participants randomly assigned , and an experimental group . This is the most basic element of a true experiment. The next decision a researcher must make is when they need to gather data during their experiment. Do they take a baseline measurement and then a measurement after treatment, or just a measurement after treatment, or do they handle measurement another way? Below, we’ll discuss the three main types of true experimental designs. There are sub-types of each of these designs, but here, we just want to get you started with some of the basics.

Using a true experiment in social work research is often pretty difficult, since as I mentioned earlier, true experiments can be quite resource intensive. True experiments work best with relatively large sample sizes, and random assignment, a key criterion for a true experimental design, is hard (and unethical) to execute in practice when you have people in dire need of an intervention. Nonetheless, some of the strongest evidence bases are built on true experiments.

For the purposes of this section, let’s bring back the example of CBT for the treatment of social anxiety. We have a group of 500 individuals who have agreed to participate in our study, and we have randomly assigned them to the control and experimental groups. The folks in the experimental group will receive CBT, while the folks in the control group will receive more unstructured, basic talk therapy. These designs, as we talked about above, are best suited for explanatory research questions.

Before we get started, take a look at the table below. When explaining experimental research designs, we often use diagrams with abbreviations to visually represent the experiment. Table 13.1 starts us off by laying out what each of the abbreviations mean.

Table 13.1 Experimental research design notations

Pretest and post-test control group design

In  pretest and post-test control group design , participants are given a  pretest of some kind to measure their baseline state before their participation in an intervention. In our social anxiety experiment, we would have participants in both the experimental and control groups complete some measure of social anxiety—most likely an established scale and/or a structured interview—before they start their treatment. As part of the experiment, we would have a defined time period during which the treatment would take place (let’s say 12 weeks, just for illustration). At the end of 12 weeks, we would give both groups the same measure as a  post-test . 

Figure 13.1 Pretest and post-test control group design

In the diagram, RA (random assignment group A) is the experimental group and RB is the control group. O 1  denotes the pre-test, X e  denotes the experimental intervention, and O 2  denotes the post-test. Let’s look at this diagram another way, using the example of CBT for social anxiety that we’ve been talking about.

Figure 13.2 Pretest and post-test control group design testing CBT an intervention

In a situation where the control group received treatment as usual instead of no intervention, the diagram would look this way, with X i  denoting treatment as usual (Figure 13.3).

Figure 13.3 Pretest and post-test control group design with treatment as usual instead of no treatment

Hopefully, these diagrams provide you a visualization of how this type of experiment establishes  time order , a key component of a causal relationship. Did the change occur after the intervention? Assuming there is a change in the scores between the pretest and post-test, we would be able to say that yes, the change did occur after the intervention. Causality can’t exist if the change happened before the intervention—this would mean that something else led to the change, not our intervention.

Post-test only control group design

Post-test only control group design involves only giving participants a post-test, just like it sounds (Figure 13.4).

Figure 13.4 Post-test only control group design

But why would you use this design instead of using a pretest/post-test design? One reason could be the testing effect that can happen when research participants take a pretest. In research, the  testing effect refers to “measurement error related to how a test is given; the conditions of the testing, including environmental conditions; and acclimation to the test itself” (Engel & Schutt, 2017, p. 444)\(^1\) (When we say “measurement error,” all we mean is the accuracy of the way we measure the dependent variable.) Figure 13.4 is a visualization of this type of experiment. The testing effect isn’t always bad in practice—our initial assessments might help clients identify or put into words feelings or experiences they are having when they haven’t been able to do that before. In research, however, we might want to control its effects to isolate a cleaner causal relationship between intervention and outcome.

Going back to our CBT for social anxiety example, we might be concerned that participants would learn about social anxiety symptoms by virtue of taking a pretest. They might then identify that they have those symptoms on the post-test, even though they are not new symptoms for them. That could make our intervention look less effective than it actually is.

However, without a baseline measurement establishing causality can be more difficult. If we don’t know someone’s state of mind before our intervention, how do we know our intervention did anything at all? Establishing  time order is thus a little more difficult. You must balance this consideration with the benefits of this type of design.

Solomon four group design

One way we can possibly measure how much the testing effect might change the results of the experiment is with the Solomon four group design. Basically, as part of this experiment, you have two control groups and two experimental groups. The first pair of groups receives both a pretest and a post-test. The other pair of groups receives only a post-test (Figure 13.5). This design helps address the problem of establishing time order in post-test only control group designs.

Figure 13.5 Solomon four-group design

For our CBT project, we would randomly assign people to four different groups instead of just two. Groups A and B would take our pretest measures and our post-test measures, and groups C and D would take only our post-test measures. We could then compare the results among these groups and see if they’re significantly different between the folks in A and B, and C and D. If they are, we may have identified some kind of testing effect, which enables us to put our results into full context. We don’t want to draw a strong causal conclusion about our intervention when we have major concerns about testing effects without trying to determine the extent of those effects.

Solomon four group designs are less common in social work research, primarily because of the logistics and resource needs involved. Nonetheless, this is an important experimental design to consider when we want to address major concerns about testing effects.

Key Takeaways

• True experimental design is best suited for explanatory research questions.
• True experiments require random assignment of participants to control and experimental groups.
• Pretest/post-test research design involves two points of measurement—one pre-intervention and one post-intervention.
• Post-test only research design involves only one point of measurement—post-intervention. It is a useful design to minimize the effect of testing effects on our results.
• Solomon four group research design involves both of the above types of designs, using 2 pairs of control and experimental groups. One group receives both a pretest and a post-test, while the other receives only a post-test. This can help uncover the influence of testing effects.
• Think about a true experiment you might conduct for your research project. Which design would be best for your research, and why?
• What challenges or limitations might make it unrealistic (or at least very complicated!) for you to carry your true experimental design in the real-world as a student researcher?
• What hypothesis(es) would you test using this true experiment?

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Methodology

• Guide to Experimental Design | Overview, Steps, & Examples

Guide to Experimental Design | Overview, 5 steps & Examples

Published on December 3, 2019 by Rebecca Bevans . Revised on June 21, 2023.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design create a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying.

There are five key steps in designing an experiment:

• Consider your variables and how they are related
• Write a specific, testable hypothesis
• Design experimental treatments to manipulate your independent variable
• Assign subjects to groups, either between-subjects or within-subjects
• Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any  extraneous variables that might influence your results. If random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead. This minimizes several types of research bias, particularly sampling bias , survivorship bias , and attrition bias as time passes.

Table of contents

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, other interesting articles, frequently asked questions about experiments.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Then you need to think about possible extraneous and confounding variables and consider how you might control  them in your experiment.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

• Systematically and precisely manipulate the independent variable(s).
• Precisely measure the dependent variable(s).
• Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalized and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

• just slightly above the natural range for your study region.
• over a wider range of temperatures to mimic future warming.
• over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

• a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
• a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

• A completely randomized design vs a randomized block design .
• A between-subjects design vs a within-subjects design .

Randomization

An experiment can be completely randomized or randomized within blocks (aka strata):

• In a completely randomized design , every subject is assigned to a treatment group at random.
• In a randomized block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

Sometimes randomization isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs. within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomizing or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

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Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimize research bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalized to turn them into measurable observations.

• Ask participants to record what time they go to sleep and get up each day.
• Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Likert scale

Research bias

• Implicit bias
• Framing effect
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

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• A Quick Guide to Experimental Design | 5 Steps & Examples

A Quick Guide to Experimental Design | 5 Steps & Examples

Published on 11 April 2022 by Rebecca Bevans . Revised on 5 December 2022.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design means creating a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying. 

There are five key steps in designing an experiment:

• Consider your variables and how they are related
• Write a specific, testable hypothesis
• Design experimental treatments to manipulate your independent variable
• Assign subjects to groups, either between-subjects or within-subjects
• Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any  extraneous variables that might influence your results. If if random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead.

Table of contents

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, frequently asked questions about experimental design.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Then you need to think about possible extraneous and confounding variables and consider how you might control  them in your experiment.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

• Systematically and precisely manipulate the independent variable(s).
• Precisely measure the dependent variable(s).
• Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalised and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

• just slightly above the natural range for your study region.
• over a wider range of temperatures to mimic future warming.
• over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

• a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
• a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

• A completely randomised design vs a randomised block design .
• A between-subjects design vs a within-subjects design .

Randomisation

An experiment can be completely randomised or randomised within blocks (aka strata):

• In a completely randomised design , every subject is assigned to a treatment group at random.
• In a randomised block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

Sometimes randomisation isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomising or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimise bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalised to turn them into measurable observations.

• Ask participants to record what time they go to sleep and get up each day.
• Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

• A testable hypothesis
• One or more independent variables that you will manipulate
• One or more dependent variables that you will measure

When designing the experiment, first decide:

• How your variable(s) will be manipulated
• How you will control for any potential confounding or lurking variables
• How many subjects you will include
• How you will assign treatments to your subjects

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.

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Experimental Research

• First Online: 25 February 2021

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• C. George Thomas 2  

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Experiments are part of the scientific method that helps to decide the fate of two or more competing hypotheses or explanations on a phenomenon. The term ‘experiment’ arises from Latin, Experiri, which means, ‘to try’. The knowledge accrues from experiments differs from other types of knowledge in that it is always shaped upon observation or experience. In other words, experiments generate empirical knowledge. In fact, the emphasis on experimentation in the sixteenth and seventeenth centuries for establishing causal relationships for various phenomena happening in nature heralded the resurgence of modern science from its roots in ancient philosophy spearheaded by great Greek philosophers such as Aristotle.

The strongest arguments prove nothing so long as the conclusions are not verified by experience. Experimental science is the queen of sciences and the goal of all speculation . Roger Bacon (1214–1294)

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• Experimental Research Designs: Types, Examples & Methods

Experimental research is the most familiar type of research design for individuals in the physical sciences and a host of other fields. This is mainly because experimental research is a classical scientific experiment, similar to those performed in high school science classes.

Imagine taking 2 samples of the same plant and exposing one of them to sunlight, while the other is kept away from sunlight. Let the plant exposed to sunlight be called sample A, while the latter is called sample B.

If after the duration of the research, we find out that sample A grows and sample B dies, even though they are both regularly wetted and given the same treatment. Therefore, we can conclude that sunlight will aid growth in all similar plants.

What is Experimental Research?

Experimental research is a scientific approach to research, where one or more independent variables are manipulated and applied to one or more dependent variables to measure their effect on the latter. The effect of the independent variables on the dependent variables is usually observed and recorded over some time, to aid researchers in drawing a reasonable conclusion regarding the relationship between these 2 variable types.

The experimental research method is widely used in physical and social sciences, psychology, and education. It is based on the comparison between two or more groups with a straightforward logic, which may, however, be difficult to execute.

Mostly related to a laboratory test procedure, experimental research designs involve collecting quantitative data and performing statistical analysis on them during research. Therefore, making it an example of quantitative research method .

What are The Types of Experimental Research Design?

The types of experimental research design are determined by the way the researcher assigns subjects to different conditions and groups. They are of 3 types, namely; pre-experimental, quasi-experimental, and true experimental research.

Pre-experimental Research Design

In pre-experimental research design, either a group or various dependent groups are observed for the effect of the application of an independent variable which is presumed to cause change. It is the simplest form of experimental research design and is treated with no control group.

Although very practical, experimental research is lacking in several areas of the true-experimental criteria. The pre-experimental research design is further divided into three types

• One-shot Case Study Research Design

In this type of experimental study, only one dependent group or variable is considered. The study is carried out after some treatment which was presumed to cause change, making it a posttest study.

• One-group Pretest-posttest Research Design: 

This research design combines both posttest and pretest study by carrying out a test on a single group before the treatment is administered and after the treatment is administered. With the former being administered at the beginning of treatment and later at the end.

• Static-group Comparison: 

In a static-group comparison study, 2 or more groups are placed under observation, where only one of the groups is subjected to some treatment while the other groups are held static. All the groups are post-tested, and the observed differences between the groups are assumed to be a result of the treatment.

Quasi-experimental Research Design

  The word “quasi” means partial, half, or pseudo. Therefore, the quasi-experimental research bearing a resemblance to the true experimental research, but not the same.  In quasi-experiments, the participants are not randomly assigned, and as such, they are used in settings where randomization is difficult or impossible.

 This is very common in educational research, where administrators are unwilling to allow the random selection of students for experimental samples.

Some examples of quasi-experimental research design include; the time series, no equivalent control group design, and the counterbalanced design.

True Experimental Research Design

The true experimental research design relies on statistical analysis to approve or disprove a hypothesis. It is the most accurate type of experimental design and may be carried out with or without a pretest on at least 2 randomly assigned dependent subjects.

The true experimental research design must contain a control group, a variable that can be manipulated by the researcher, and the distribution must be random. The classification of true experimental design include:

• The posttest-only Control Group Design: In this design, subjects are randomly selected and assigned to the 2 groups (control and experimental), and only the experimental group is treated. After close observation, both groups are post-tested, and a conclusion is drawn from the difference between these groups.
• The pretest-posttest Control Group Design: For this control group design, subjects are randomly assigned to the 2 groups, both are presented, but only the experimental group is treated. After close observation, both groups are post-tested to measure the degree of change in each group.
• Solomon four-group Design: This is the combination of the pretest-only and the pretest-posttest control groups. In this case, the randomly selected subjects are placed into 4 groups.

The first two of these groups are tested using the posttest-only method, while the other two are tested using the pretest-posttest method.

Examples of Experimental Research

Experimental research examples are different, depending on the type of experimental research design that is being considered. The most basic example of experimental research is laboratory experiments, which may differ in nature depending on the subject of research.

Administering Exams After The End of Semester

During the semester, students in a class are lectured on particular courses and an exam is administered at the end of the semester. In this case, the students are the subjects or dependent variables while the lectures are the independent variables treated on the subjects.

Only one group of carefully selected subjects are considered in this research, making it a pre-experimental research design example. We will also notice that tests are only carried out at the end of the semester, and not at the beginning.

Further making it easy for us to conclude that it is a one-shot case study research. 

Employee Skill Evaluation

Before employing a job seeker, organizations conduct tests that are used to screen out less qualified candidates from the pool of qualified applicants. This way, organizations can determine an employee’s skill set at the point of employment.

In the course of employment, organizations also carry out employee training to improve employee productivity and generally grow the organization. Further evaluation is carried out at the end of each training to test the impact of the training on employee skills, and test for improvement.

Here, the subject is the employee, while the treatment is the training conducted. This is a pretest-posttest control group experimental research example.

Evaluation of Teaching Method

Let us consider an academic institution that wants to evaluate the teaching method of 2 teachers to determine which is best. Imagine a case whereby the students assigned to each teacher is carefully selected probably due to personal request by parents or due to stubbornness and smartness.

This is a no equivalent group design example because the samples are not equal. By evaluating the effectiveness of each teacher’s teaching method this way, we may conclude after a post-test has been carried out.

However, this may be influenced by factors like the natural sweetness of a student. For example, a very smart student will grab more easily than his or her peers irrespective of the method of teaching.

What are the Characteristics of Experimental Research?  

Experimental research contains dependent, independent and extraneous variables. The dependent variables are the variables being treated or manipulated and are sometimes called the subject of the research.

The independent variables are the experimental treatment being exerted on the dependent variables. Extraneous variables, on the other hand, are other factors affecting the experiment that may also contribute to the change.

The setting is where the experiment is carried out. Many experiments are carried out in the laboratory, where control can be exerted on the extraneous variables, thereby eliminating them. 

Other experiments are carried out in a less controllable setting. The choice of setting used in research depends on the nature of the experiment being carried out.

• Multivariable

Experimental research may include multiple independent variables, e.g. time, skills, test scores, etc.

Why Use Experimental Research Design?  

Experimental research design can be majorly used in physical sciences, social sciences, education, and psychology. It is used to make predictions and draw conclusions on a subject matter. 

Some uses of experimental research design are highlighted below.

• Medicine: Experimental research is used to provide the proper treatment for diseases. In most cases, rather than directly using patients as the research subject, researchers take a sample of the bacteria from the patient’s body and are treated with the developed antibacterial

The changes observed during this period are recorded and evaluated to determine its effectiveness. This process can be carried out using different experimental research methods.

• Education: Asides from science subjects like Chemistry and Physics which involves teaching students how to perform experimental research, it can also be used in improving the standard of an academic institution. This includes testing students’ knowledge on different topics, coming up with better teaching methods, and the implementation of other programs that will aid student learning.
• Human Behavior: Social scientists are the ones who mostly use experimental research to test human behaviour. For example, consider 2 people randomly chosen to be the subject of the social interaction research where one person is placed in a room without human interaction for 1 year.

The other person is placed in a room with a few other people, enjoying human interaction. There will be a difference in their behaviour at the end of the experiment.

• UI/UX: During the product development phase, one of the major aims of the product team is to create a great user experience with the product. Therefore, before launching the final product design, potential are brought in to interact with the product.

For example, when finding it difficult to choose how to position a button or feature on the app interface, a random sample of product testers are allowed to test the 2 samples and how the button positioning influences the user interaction is recorded.

What are the Disadvantages of Experimental Research?  

• It is highly prone to human error due to its dependency on variable control which may not be properly implemented. These errors could eliminate the validity of the experiment and the research being conducted.
• Exerting control of extraneous variables may create unrealistic situations. Eliminating real-life variables will result in inaccurate conclusions. This may also result in researchers controlling the variables to suit his or her personal preferences.
• It is a time-consuming process. So much time is spent on testing dependent variables and waiting for the effect of the manipulation of dependent variables to manifest.
• It is expensive. 
• It is very risky and may have ethical complications that cannot be ignored. This is common in medical research, where failed trials may lead to a patient’s death or a deteriorating health condition.
• Experimental research results are not descriptive.
• Response bias can also be supplied by the subject of the conversation.
• Human responses in experimental research can be difficult to measure. 

What are the Data Collection Methods in Experimental Research?  

Data collection methods in experimental research are the different ways in which data can be collected for experimental research. They are used in different cases, depending on the type of research being carried out.

1. Observational Study

This type of study is carried out over a long period. It measures and observes the variables of interest without changing existing conditions.

When researching the effect of social interaction on human behavior, the subjects who are placed in 2 different environments are observed throughout the research. No matter the kind of absurd behavior that is exhibited by the subject during this period, its condition will not be changed.

This may be a very risky thing to do in medical cases because it may lead to death or worse medical conditions.

2. Simulations

This procedure uses mathematical, physical, or computer models to replicate a real-life process or situation. It is frequently used when the actual situation is too expensive, dangerous, or impractical to replicate in real life.

This method is commonly used in engineering and operational research for learning purposes and sometimes as a tool to estimate possible outcomes of real research. Some common situation software are Simulink, MATLAB, and Simul8.

Not all kinds of experimental research can be carried out using simulation as a data collection tool . It is very impractical for a lot of laboratory-based research that involves chemical processes.

A survey is a tool used to gather relevant data about the characteristics of a population and is one of the most common data collection tools. A survey consists of a group of questions prepared by the researcher, to be answered by the research subject.

Surveys can be shared with the respondents both physically and electronically. When collecting data through surveys, the kind of data collected depends on the respondent, and researchers have limited control over it.

Formplus is the best tool for collecting experimental data using survey s. It has relevant features that will aid the data collection process and can also be used in other aspects of experimental research.

Differences between Experimental and Non-Experimental Research 

1. In experimental research, the researcher can control and manipulate the environment of the research, including the predictor variable which can be changed. On the other hand, non-experimental research cannot be controlled or manipulated by the researcher at will.

This is because it takes place in a real-life setting, where extraneous variables cannot be eliminated. Therefore, it is more difficult to conclude non-experimental studies, even though they are much more flexible and allow for a greater range of study fields.

2. The relationship between cause and effect cannot be established in non-experimental research, while it can be established in experimental research. This may be because many extraneous variables also influence the changes in the research subject, making it difficult to point at a particular variable as the cause of a particular change

3. Independent variables are not introduced, withdrawn, or manipulated in non-experimental designs, but the same may not be said about experimental research.

Conclusion  

Experimental research designs are often considered to be the standard in research designs. This is partly due to the common misconception that research is equivalent to scientific experiments—a component of experimental research design.

In this research design, one or more subjects or dependent variables are randomly assigned to different treatments (i.e. independent variables manipulated by the researcher) and the results are observed to conclude. One of the uniqueness of experimental research is in its ability to control the effect of extraneous variables.

Experimental research is suitable for research whose goal is to examine cause-effect relationships, e.g. explanatory research. It can be conducted in the laboratory or field settings, depending on the aim of the research that is being carried out. 

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• Bean Seed Germination Experiment Results
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• Experiment: Flame Test and Chemical Fingerprinting
• “Stanford Prison Experiment Ethics” by Philip Zimbardo
• Archimedes’ Principle Experiment: Determining Gravity of Objects
• Water Quality and Contamination Experiment Report
• Ideal Gas Expansion Law: Experiment The purpose of the experiment was to understand the differences between different types of ideal gas expansions, paying attention to the amount of work done.
• Metal and Non-metal Redox Reactions Experiment The following experiment aimed to investigate Redox reaction and hence determine which elements were reactive; metal v. metal redox reactions, and non-metal v. non-metal reactions.
• Human Transport Systems: The Pulse Rate Experiment The report provides an analysis of the pulse rate experiment aimed at determining the pulse rates before and after a five-minute exercise conducted by the researcher.
• Hawthorne Experiments – Elton Mayo With Roethlisberger and Dickson The Hawthorne theories have brought about a positive change in the behavior and attitude of the managers as well as the workers.
• Fiji Water Quality: Biology Lab Experiment Since Fiji water is among the popular brands in the US, it is essential to evaluate whether it is clean, that is, safe for human consumption.
• John Watson and the “Little Albert” Experiment John Watson is considered to be the founder of behaviorism, a psychological theory that focuses on visible behavior while diminishing the notion of consciousness.
• Scientific Report Draft on Osmosis Egg Experiment Understanding how an egg reacts when placed in solutions of different concentrations enables one to understand the role of osmosis in the human body.
• Why People Obey Authority: Milgram Experiment and Real-World Situation Human beings would obey authority depending on the overall rewards, potential personal gains, and the consequences of failing to do so.
• Experiment on Effect of Energy Drinks on Athletic Performance Experimental research is a study that a researcher sets up to evaluate a given situation, such as a drug or treatment intervention.
• Inductor-Capacitor-Resistor Circuit Experiment The article presents the experiment that will demonstrate the relationship between an inductor, voltmeter, and resistor in an inductor-capacitor-resistor (LCR) circuit.
• Air Pressure Experiment Methods and Results The plastic mesh fabric was placed over the mouth of the Mason jar, and the metal screw band of the latter was fastened firmly over the plastic mesh sheet.
• Putnam’s “Twin Earth” Thought-Experiment Throughout the history of analytic philosophy, the problem of meaning has been and remains one of its central themes.
• Chemical Experiment on Enzyme Amylase This paper presents an experiment that was conducted to determine the activity of amylase on starch at various pH levels.
• An Observable Experiment: Control Over the Variables An observable experiment is defined as the experiment in which the independent variables cannot possibly be controlled by the person or person setting the test.
• Miles Davis and Steve Reich: Geniuses of Experiments and Creativity Although Miles Davis’ and Steve Reich’s music belongs to different genres, they are connected in their constant search for a new sound by experimenting and improvising.
• Unethical Research Experiments Violation of ethical principles can be traced in two analyzed cases; only in Landis’s experiment harm and killing were real in relation to animals.
• Kant’s Ethical Philosophy and Milgram’s Experiments The problem for Kant’s ethical philosophy is whether moral principles are applicable to nonhumans, such as Galacticans.
• Helicopter Experiment Assessment This report of a paper helicopter experiment involved designating a paper helicopter in varied designs and then dropping it severally while recording the flight time.
• Ideal Experiment Design: Independent and Dependent Variables This work describes the ideal experiment, that is designed to verify the causal relationship between independent and dependent variables.
• Social Experiment: Informal Norms of Gender Issues The social experiment presents a contradiction between the socially-accepted norms and the understanding of equality between men and women.
• Acoustics Experiment in Brunel’s Thames Tunnel In this project, tunnels that exist below London streets for a variety of communications, civil defense, and military purposes will be used as the objects of the experiment.
• The Milgram Experiment: Ethical Issues The Milgram experiment is a controversial study on the subject of obedience to authority figures. The participants were asked to deliver electric shocks to other people.
• Milgram Experiment: The Question of Ethics This essay will discuss the Milgram experiment and also argue that it was ethical as medical research standards were met, and no undue harm to the participants was caused.
• Ethical Implications of the Early Studies in Psychology: Milgram’s Experiment Milgram’s experiment on obedience content and results are valuable for understanding the ethical issues that may occur in social and behavioral research.
• P. Zimbardo’s Stanford Experiment A psychological experiment is an event conducted to acquire new scientific knowledge about psychology through the researcher’s deliberate intervention in the life of the examinee.
• Osmosis Experiment With Parsnip Through Differing Concentration of Sucrose
• Identifying the Benefits of Home Ownership: A Swedish Experiment
• Experiment for Cancer Risk Factors
• Hydrochloric Acid Into Tubes of Water and Sodium Thiosulphate Experiment
• General Information about Monkey Drug Trials Experiment
• Reaction Rates Experiment Hydrochloric Acid
• Hydrochloric Acid and Marble Chips Experiment
• Physical Disability and Labor Market Discrimination: Evidence From a Field Experiment
• Canadian Advanced Nanosatellite Experiment Biology
• Dr. Heidegger’s Experiment: Reality or Illusion
• Experiment and Multi-Grid Modeling of Evacuation From a Classroom
• High-Performance Liquid Chromatography Experiment
• Social Capital and Contributions in a Public-Goods Experiment
• Illusory Gains From Chile’s Targeted School Voucher Experiment
• Short Selling and Earnings Management: A Controlled Experiment
• Theft and Rural Poverty: Results of a Natural Experiment
• Lab Experiment: The Effectiveness of Different Antibiotics on Bacteria
• Brucellosis and Its Treatment: Experiment With Doxycycline
• The Link Between Stanford Prison Experiment and Milgram Study
• Four Fundamental Results From the Mice Experiment
• “Tuskegee Syphilis Experiment – The Deadly Deception”: Unethical Scientific Experiment “Tuskegee Syphilis Experiment – The Deadly Deception” reviews an unethical scientific experiment on humans that was conducted by White physicians on African-Americans.
• A Hypothesis and an Experiment: A Case Study On the control experiment, there would be a seed grown at normal aeration, and wind conditions. All should have a viable bean seed planted centrally on watered soil preferably.
• Extraneous Variables in Experiments There are some variables in experiments besides the independent variables that usually cause a variation or a change to the dependent variables.
• Virtue Ethics in Stanford and Milgram’s Experiments This paper investigates the notion of virtue ethics, discussing two major studies, the Stanford prison experiment, and Milgram’s obedience studies.
• Bolted & Welded Connections and Tension Experiment Exploring and comparing the expected and actual failure modes of both bottled and welded connections in tension are the primary purposes of the paper.
• The Use of Animals in Psychological Experiments The method of experimentation is of great significance for multiple fields of psychology, especially for the behaviorist branch.
• Medical Pharmacology: The Langendorff Experiment The Langendorff experiment aimed at using an ex vivo isolated rat heart preparation to demonstrate the pharmacological effects of two unknown drugs.
• Studying Organisations: The Hawthorne Experiments The Hawthorn experiments marked a new direction in research of motivation and productivity. More than half a century has passed, and productivity remains a concern of management.
• Metrology Experiment with Measurement Tools The experiment concerned testing the efficacy of the measurement tools such as the Vernier caliper, a depth gauge, a micrometer, and a gauge in an uncertainty analysis.
• Conducting a Titration Experiment Titration studies are conducted to quantify the amount of an unidentified element in the sample using a methodological approach.
• Thought Experiment: The Morality of Human Actions A thought experiment aimed at assessing the morality of human actions motivated by divine punishment or reward raises the question of morality and religion correlation.
• Lab Experiment on Animals’ Taste or Smell Senses The hypothesis of the study is that taste perception and detection of different sugars by insects were similar to that of humans.
• The Stanford Prison Experiment The Stanford prison experiment is an example of how outside social situations influence changes in thought and behavior among humans.
• Pasture Experiment: Fertiliser Treatments Response This work is an experiment that defines the role of fertilizers in pasture production and to establish the appropriate use of pasture sampling to assess pasture mass.
• Scientific Experiments on Animals from Ethical Perspectives This paper discusses using animals in scientific experiments from the consequentialist, Kantian deontological and Donna Yarri’s Christian character-based perspectives.
• The Stanford Prison Experiment Analysis Abuse between guards and prisoners is an imminent factor attributed to the differential margin on duties and responsibilities.
• The Stanford Prison Experiment’s Historical Record The Stanford Prison Experiment is a seminal investigation into the dynamics of peer pressure in human psychology.
• Socioeconomic Status and Sentencing Severity Experiment There are two types of validity threats: external and internal. External validity refers to the degree to which the study can be applied to situations outside the research context.
• Psychology: Zimbardo Prison Experiment Despite all the horrors that contradict ethics, Zimbardo’s research contributed to the formation of social psychology. It was unethical to conduct this experiment.
• Post-Covid Adaptation Laboratory Experiment The goal of the laboratory experiment that this paper will outline is to test the hypothesis about the needs of senior citizens in the post-pandemic era.
• Psychology: Milgram Obedience Experiment Milgram’s experiment may be the last psychological experiment that has had a significant impact on psychology and public opinion.
• Predicting the Replicability of Social Science Lab Experiments The quality of work is the most significant factor for any academic organization. A research process for any scientific project requires careful evaluation of information sources.
• Moral Dilemma and Thought Experiments The aim of this essay is to set up a thought experiment in which a moral dilemma must be resolved. A person is invited to make a choice as a result of which people should suffer.
• Experiments in High-Frequency Trading High-frequency trading (HFT) is becoming increasingly popular with private businesses and traders. HFT allows traders to make transactions within fractions of seconds.
• The Ethical Issues in 1940’s U.S. Experiments With Syphilis in Guatemala The Guatemala tests have been viewed as a dark side of the U.S. clinical examination: in the 1940s, they purposely uncovered over 5,000 individuals with syphilis and gonorrhea.
• Isopods and Their Use in Experiments Isopod is a large family belonging to the crayfish order. The fact that isopods are good to use in various experiments is related to their habitat.
• Sociological Experiment: The Salience of Social Norms Based on the sociological experiment described in the paper, the author demonstrated the salience of social norms that exist in our culture.
• Blue-Eyed vs. Brown-Eyed Experiment Elliot exposed the learners to discrimination, in which blue-eyed children were initially preferred and given more privileges in the classroom than brown-eyed students.
• Experiment: Science Meets Real Life The experiment involves the sequential study of the dog’s behavior and its reaction to a change in some factors, such as food and bowl.
• Should Animals Be Used for Scientific Experiments? Unfortunately, at the moment, the use of animals in science and medicine cannot be excluded entirely. However, it is possible to conduct experiments using mathematical models.
• Smoking: An Idea for a Statistical Experiment The hypothesis is that people who smoke cigarettes daily tend to earn more than others: this is a personal observation that requires careful experimental testing.
• The Stanford Jail Experiment Critiques One of the most important critiques leveled at the Stanford Jail Experiment is the length of time it took Zimbardo to call a halt to the experiment.
• Can Nonrandomized Experiments Yield Accurate Answers?
• What Kind of Experiments Are Done on Animals?
• Is It Good to Use Animals for Experiments?
• What Are the Types of Experiments?
• Is There Any Healthy Way to Experiment With Drugs?
• What Are the Top Experiments of All Time?
• Are Breaching Experiments Ethical?
• What Does It Mean to Experiment With a Drug?
• Why Do We Use Factorial Experiments?
• How Does Temperature Affect the Rate of Reaction Experiment?
• What Are the Easiest Experiments to Do?
• How Can Rushing Harm the Data and the Experiment Overall?
• What Are the Steps to a Science Experiment?
• How Do Errors Affect the Experiment?
• What Is the Purpose of the Wax Experiment and What Conclusion Does Descartes Reach on Its Basis?
• Can an Experiment Be Invalid but Reliable?
• What Is the Most Influential Experiment in Psychology?
• Why Are Fruit Flies Used for Experiments?
• How Can You Improve the Accuracy of an Experiment?
• What Was Galileo’s Famous Cannonball Drop Experiment?
• What Can Knowledge Be Gained From Conducting a Breaching Experiment?
• How Do You Identify the Independent and Dependent Variables in an Experiment?
• What Was Griffith’s Experiment and Why Was It Important?
• What Is the Difference Between Contingent Valuation and Choice Experiment?
• What Is the Choice Experiment Valuation Method?
• Super Size Me and Jogn Cisna Experiments In comparison to Super Size Me, the experiment of John Cisna immediately stands out with a positive attitude towards fast food.
• Health and Medicine: Experiments and Discussions In the first experiment, researchers tested the subjectivity of polygraph examiners’ assessments. The specialist was given a specific name before the test began to do it.
• Stanford Prison Experiment: Behind the Mask Stanford Prison Experiment organized by Stanford researcher Philip Zimbardo led to a strong public response and still discussed today.
• An Experiment in DNA Cloning and Sequencing The aim of this experiment is to clone a fragment of DNA that includes the Green Fluorescent Protein (GFP) gene into the vector pTTQ18, which is an expression vector.
• An Enzyme Linked Immunosorbent Assay Experiment In our society presently, immunoassay techniques used in data analyses have assumed a place of high significance, particularly as it applies to pure/applied research.
• Anaerobic Threshold: An Experiment Anaerobic Threshold refers to the minimum level below which no increase in blood lactose can occur. At levels above AT, supplementing aerobic production needs aerobic energy.
• Comparative Effectiveness of Various Surfactants: Experiment Surfactants refer to chemical substances that lessen the surface tension in water. This experiment aimed at establishing the comparative effectiveness of various surfactants.
• An Experiment on Data Mining Extend This experiment aims to utilize knowledge and principles of data mining in depicting the investigation of emergent data in biology- particularly on the development of ELISAs.
• Lab Experiment on Photovoltaics The experiment was done specifically to ascertain how various connected units could be coordinated to give a more reliable and controllable functioning.
• Mind Control: Ethics of the Experiment The topics of mind control and free will has always been seen as a morally grey area in terms of its research potential.
• A Personal Behavior Modification Experiment Using Operant Conditioning This research paper points out the positive outcomes of swearing: it can relieve stress and help one cope with emotional work.
• Jane Elliott’s Experiment on Discrimination The teacher Jane Elliott from Iowa decided to conduct an experiment demonstrating to her students what discrimination is and what it feels like.
• The Tuskegee Syphilis Experiment When the Tuskegee Syphilis Experiment was begun, over 75 years ago, no such principles were officially in place.
• The Power of Conformity: Asch’s Experiments The article examines a series of experiments by Asch that helped him identify the factors influencing social conformity.
• The Critical Characteristics of an Experiment The main aim of this assignment is to evaluate the thought control experiment by famous psychologist Ellen Langer and determine whether it is a qualitative experiment.
• Ethical Analysis of the Tuskegee Syphilis Experiments The Tuskegee Syphilis Study failed to take into account several critical ethical considerations. This essay examines some of the ethical problems linked to the investigation.
• Boston’s Experiment: Harvard Business Review’s Lessons In Harvard Business Review’s Lessons from Boston’s Experiment with The One Fund, Mitchell discusses his experience with fund distribution to the victims of the Boston bombing.
• The Stanford Prison Experiment Review The video presents an experiment held in 1971. In general, a viewer can observe that people are subjected to behavior and opinion change when affected by others.
• The Way to Come To Terms With Yourself: Social Distancing Experiment In this work, the author describes the course and results of an experiment on social distance: refusal to use gadgets, any communication, and going out.
• Experiment: Bacteria vs Antibiotics The experiment aimed was to test the reaction of bacteria towards some antibiotics and determine the effectiveness of those antibiotics in treating some diseases.
• Ethics: Experiments on Animals Industrial and biomedical research is often painful and most of the test ends up killing the animals. Experiments such as these often incur the wrath of the animal rights movement.
• Impact of the Stanford Prison Experiment Have on Psychology This essay will begin with a brief description of Zimbardo’s Stanford Prison Experiment then it will move to explore two main issues that arose from the said experiment.
• Chemistry of Cooking. Saffron Rice Experiment This research project outlines an experiment that aims to determine the temperature at which Saffron rice turns yellow.
• Worldview Changes After the Blindness Experiment Our senses are the central source of information about the world and events that happen around us. So, the loss of one of these is a significant challenge for a person.
• Evaluation of the Stanford Prison Experiment’ Role The Stanford Prison Experiment is a study that was conducted on August 20, 1971 by a group of researchers headed by the psychology professor Philip Zimbardo.
• Social Experiment: Wrong Outfit in a Wedding Event The attendees of the wedding event displayed disappointment, discomfort, and open resentment towards the dressing style.
• Heat Transfer Rates in a Hot Jet: Experiment The experiment is aimed at determining the heat transfer rates in a hot jet. The reasons for the hot jet to have different heat rates in different areas will be determined.
• Inattentive Blindness in Psychological Experiment The features of the human consciousness not to notice quite obvious changes are natural and innate. Such blindness can be caused by several factors.
• Situation, Institutional Norms, and Roles: The Stanford Experiment of Zimbardo Philip Zimbardo’s Stanford Experiment brought him critical acclaim. At the same time, it accorded him a certain level of notoriety; because of the methodologies he utilized to conduct the experiment.
• Tuskegee Syphilis Experiment: Ethical Controversy Tuskegee case set the background for the reconsideration of healthcare ethics, which means that the ethical value of the given case deserves reconsideration.
• Gender Stereotyping Experiment: The Level of Gender Stereotyping in Society The present study measures the effects of stereotyping women. It examines the first impression formed by subjects based on the information about a fictitious man or a woman.
• Psychological Studies and Experiments: Code of Conduct The following paper is based on past psychological studies i.e. Stanly Milgram’s ‘Obedience Experiment’, Philip Zimbardo’s ‘Stanford Prison Experiment, and Jane Elliott’s ‘Class Divided’.
• Using Animals in Medical Experiments This paper explores how the principles of the character-based ethical approach can be applied to the discussion of using animals in the medical research and experiments.
• The Stanford Experiment by Philip Zimbardo Philip Zimbardo’s Stanford Experiment shows that situational power and norms dictate the behavior of the individual more than the core beliefs that made up his personal identity.

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