a simple controlled experiment

Controlled Experiment

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This is when a hypothesis is scientifically tested.

In a controlled experiment, an independent variable (the cause) is systematically manipulated, and the dependent variable (the effect) is measured; any extraneous variables are controlled.

The researcher can operationalize (i.e., define) the studied variables so they can be objectively measured. The quantitative data can be analyzed to see if there is a difference between the experimental and control groups.

What is the control group?

In experiments scientists compare a control group and an experimental group that are identical in all respects, except for one difference – experimental manipulation.

Unlike the experimental group, the control group is not exposed to the independent variable under investigation and so provides a baseline against which any changes in the experimental group can be compared.

Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

Randomly allocating participants to independent variable groups means that all participants should have an equal chance of participating in each condition.

The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.

What are extraneous variables?

The researcher wants to ensure that the manipulation of the independent variable has changed the changes in the dependent variable.

Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.

Extraneous variables should be controlled were possible, as they might be important enough to provide alternative explanations for the effects.

In practice, it would be difficult to control all the variables in a child’s educational achievement. For example, it would be difficult to control variables that have happened in the past.

A researcher can only control the current environment of participants, such as time of day and noise levels.

Why conduct controlled experiments?

Scientists use controlled experiments because they allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.

Controlled experiments also follow a standardized step-by-step procedure. This makes it easy for another researcher to replicate the study.

Key Terminology

Experimental group.

The group being treated or otherwise manipulated for the sake of the experiment.

Control Group

They receive no treatment and are used as a comparison group.

Ecological validity

The degree to which an investigation represents real-life experiences.

Experimenter effects

These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.

Demand characteristics

The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).

Independent variable (IV)

The variable the experimenter manipulates (i.e., changes) – is assumed to have a direct effect on the dependent variable.

Dependent variable (DV)

Variable the experimenter measures. This is the outcome (i.e., the result) of a study.

Extraneous variables (EV)

All variables that are not independent variables but could affect the results (DV) of the experiment. Extraneous variables should be controlled where possible.

Confounding variables

Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.

Random Allocation

Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.

Order effects

Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:

(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;

(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.

What is the control in an experiment?

In an experiment , the control is a standard or baseline group not exposed to the experimental treatment or manipulation. It serves as a comparison group to the experimental group, which does receive the treatment or manipulation.

The control group helps to account for other variables that might influence the outcome, allowing researchers to attribute differences in results more confidently to the experimental treatment.

Establishing a cause-and-effect relationship between the manipulated variable (independent variable) and the outcome (dependent variable) is critical in establishing a cause-and-effect relationship between the manipulated variable.

What is the purpose of controlling the environment when testing a hypothesis?

Controlling the environment when testing a hypothesis aims to eliminate or minimize the influence of extraneous variables. These variables other than the independent variable might affect the dependent variable, potentially confounding the results.

By controlling the environment, researchers can ensure that any observed changes in the dependent variable are likely due to the manipulation of the independent variable, not other factors.

This enhances the experiment’s validity, allowing for more accurate conclusions about cause-and-effect relationships.

It also improves the experiment’s replicability, meaning other researchers can repeat the experiment under the same conditions to verify the results.

Why are hypotheses important to controlled experiments?

Hypotheses are crucial to controlled experiments because they provide a clear focus and direction for the research. A hypothesis is a testable prediction about the relationship between variables.

It guides the design of the experiment, including what variables to manipulate (independent variables) and what outcomes to measure (dependent variables).

The experiment is then conducted to test the validity of the hypothesis. If the results align with the hypothesis, they provide evidence supporting it.

The hypothesis may be revised or rejected if the results do not align. Thus, hypotheses are central to the scientific method, driving the iterative inquiry, experimentation, and knowledge advancement process.

What is the experimental method?

The experimental method is a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.

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Ideas for Controlled Variable Science Projects

Science Projects With Three Variables for Kids in Fifth Grade

Many science projects investigate a combination of independent and controlled variables to see what happens as a result - the dependent variable. To get reliable results from your experiments, you change the independent variables carefully and the controlled variables as little as possible; this ensures that only the things you're interested in affect your experimental results.

Does Sugar Dissolve More Quickly in Warm or Cool Water?

Heat a cup of water while allowing another cup of water to remain cool. Dissolve one teaspoon of sugar in each cup of water. The controlled variable would be the number of times and the pressure used to stir the mixture because added motion of the water may or may not dissolve the sugar more quickly whether the water is warm or cool. Record the amount of undissolved sugar in the bottom of the container.

Does a Plant Grow Better in Direct or Indirect Sunlight?

A science project involving plants has controlled variables in the amount of water given to each plant and the amount and kind of soil in which the plant is living. Place one plant in direct sunlight and the other in a shaded area or indoors to conduct the science experiment. Record daily results in the height of the plant.

Will a Baby Bunny Grow Bigger When Fed Rabbit Food or Fresh Vegetables?

Two rabbits, ideally from the same litter, can be used to conduct a classroom experiment. Give each rabbit a different diet: one of only fresh vegetables such as lettuce, carrots and celery; feed the other rabbit pellets from the pet store. The controlled variable in this experiment would be the weight in food each rabbit receives even though the type of food is different. Record the height, weight and length of the two rabbits each week.

Which Will Clean a Penny Faster, Water or Vinegar?

In two glass containers, place one cup of distilled water in one and white vinegar in the other. Carefully drop a dirty penny into each container of liquid and record the changes in the penny's appearance over the course of one week. The controlled variable is in the amount of liquid used to clean each penny.

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What Is a Controlled Experiment?

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A controlled experiment is one in which everything is held constant except for one variable . Usually, a set of data is taken to be a control group , which is commonly the normal or usual state, and one or more other groups are examined where all conditions are identical to the control group and to each other except for one variable.

Sometimes it's necessary to change more than one variable, but all of the other experimental conditions will be controlled so that only the variables being examined change. And what is measured is the variables' amount or the way in which they change.

Controlled Experiment

• A controlled experiment is simply an experiment in which all factors are held constant except for one: the independent variable.
• A common type of controlled experiment compares a control group against an experimental group. All variables are identical between the two groups except for the factor being tested.
• The advantage of a controlled experiment is that it is easier to eliminate uncertainty about the significance of the results.

Example of a Controlled Experiment

Let's say you want to know if the type of soil affects how long it takes a seed to germinate, and you decide to set up a controlled experiment to answer the question. You might take five identical pots, fill each with a different type of soil, plant identical bean seeds in each pot, place the pots in a sunny window, water them equally, and measure how long it takes for the seeds in each pot to sprout.

This is a controlled experiment because your goal is to keep every variable constant except the type of soil you use. You control these features.

Why Controlled Experiments Are Important

The big advantage of a controlled experiment is that you can eliminate much of the uncertainty about your results. If you couldn't control each variable, you might end up with a confusing outcome.

For example, if you planted different types of seeds in each of the pots, trying to determine if soil type affected germination, you might find some types of seeds germinate faster than others. You wouldn't be able to say, with any degree of certainty, that the rate of germination was due to the type of soil. It might as well have been due to the type of seeds.

Or, if you had placed some pots in a sunny window and some in the shade or watered some pots more than others, you could get mixed results. The value of a controlled experiment is that it yields a high degree of confidence in the outcome. You know which variable caused or did not cause a change.

Are All Experiments Controlled?

No, they are not. It's still possible to obtain useful data from uncontrolled experiments, but it's harder to draw conclusions based on the data.

An example of an area where controlled experiments are difficult is human testing. Say you want to know if a new diet pill helps with weight loss. You can collect a sample of people, give each of them the pill, and measure their weight. You can try to control as many variables as possible, such as how much exercise they get or how many calories they eat.

However, you will have several uncontrolled variables, which may include age, gender, genetic predisposition toward a high or low metabolism, how overweight they were before starting the test, whether they inadvertently eat something that interacts with the drug, etc.

Scientists try to record as much data as possible when conducting uncontrolled experiments, so they can see additional factors that may be affecting their results. Although it is harder to draw conclusions from uncontrolled experiments, new patterns often emerge that would not have been observable in a controlled experiment.

For example, you may notice the diet drug seems to work for female subjects, but not for male subjects, and this may lead to further experimentation and a possible breakthrough. If you had only been able to perform a controlled experiment, perhaps on male clones alone, you would have missed this connection.

• Box, George E. P., et al.  Statistics for Experimenters: Design, Innovation, and Discovery . Wiley-Interscience, a John Wiley & Soncs, Inc., Publication, 2005. 
• Creswell, John W.  Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research . Pearson/Merrill Prentice Hall, 2008.
• Pronzato, L. "Optimal experimental design and some related control problems". Automatica . 2008.
• Robbins, H. "Some Aspects of the Sequential Design of Experiments". Bulletin of the American Mathematical Society . 1952.
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• Controlled Experiments | Methods & Examples of Control

Controlled Experiments | Methods & Examples of Control

Published on 19 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.

Controlling variables can involve:

• Holding variables at a constant or restricted level (e.g., keeping room temperature fixed)
• Measuring variables to statistically control for them in your analyses
• Balancing variables across your experiment through randomisation (e.g., using a random order of tasks)

Table of contents

Why does control matter in experiments, methods of control, problems with controlled experiments, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables.

• Your independent variable is the colour used in advertising.
• Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.

• Design and description of the meal
• Study environment (e.g., temperature or lighting)
• Participant’s frequency of buying fast food
• Participant’s familiarity with the specific fast food brand
• Participant’s socioeconomic status

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You can control some variables by standardising your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., advert colour) should be systematically changed between groups.

Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with colour blindness).

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment, and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

• A control group that’s presented with red advertisements for a fast food meal
• An experimental group that’s presented with green advertisements for the same fast food meal

Random assignment

To avoid systematic differences between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a ‘true experiment’ – it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers – or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs.

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses. In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses.

Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity – the extent to which your results can be generalised to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritise control or generalisability in your experiment.

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

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Microbe Notes

Controlled Experiments: Definition, Steps, Results, Uses

Controlled experiments ensure valid and reliable results by minimizing biases and controlling variables effectively.

Rigorous planning, ethical considerations, and precise data analysis are vital for successful experiment execution and meaningful conclusions.

Real-world applications demonstrate the practical impact of controlled experiments, guiding informed decision-making in diverse domains.

Controlled experiments are the systematic research method where variables are intentionally manipulated and controlled to observe the effects of a particular phenomenon. It aims to isolate and measure the impact of specific variables, ensuring a more accurate causality assessment.

Table of Contents

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Importance of controlled experiments in various fields

Controlled experiments are significant across diverse fields, including science, psychology, economics, healthcare, and technology.

They provide a systematic approach to test hypotheses, establish cause-and-effect relationships, and validate the effectiveness of interventions or solutions.

Why Controlled Experiments Matter? 

Validity and reliability of results.

Controlled experiments uphold the gold standard for scientific validity and reliability. By meticulously controlling variables and conditions, researchers can attribute observed outcomes accurately to the independent variable being tested. This precision ensures that the findings can be replicated and are trustworthy.

Minimizing Biases and Confounding Variables

One of the core benefits of controlled experiments lies in their ability to minimize biases and confounding variables. Extraneous factors that could distort results are mitigated through careful control and randomization. This enables researchers to isolate the effects of the independent variable, leading to a more accurate understanding of causality.

Achieving Causal Inference

Controlled experiments provide a strong foundation for establishing causal relationships between variables. Researchers can confidently infer causation by manipulating specific variables and observing resulting changes. The capability informs decision-making, policy formulation, and advancements across various fields.

Planning a Controlled Experiment

Formulating research questions and hypotheses.

Formulating clear research questions and hypotheses is paramount at the outset of a controlled experiment. These inquiries guide the direction of the study, defining the variables of interest and setting the stage for structured experimentation.

Well-defined questions and hypotheses contribute to focused research and facilitate meaningful data collection.

Identifying Variables and Control Groups

Identifying and defining independent, dependent, and control variables is fundamental to experimental planning. 

Precise identification ensures that the experiment is designed to isolate the effect of the independent variable while controlling for other influential factors. Establishing control groups allows for meaningful comparisons and robust analysis of the experimental outcomes.

Designing Experimental Procedures and Protocols

Careful design of experimental procedures and protocols is essential for a successful controlled experiment. The step involves outlining the methodology, data collection techniques, and the sequence of activities in the experiment. 

A well-designed experiment is structured to maintain consistency, control, and accuracy throughout the study, thereby enhancing the validity and credibility of the results.

Conducting a Controlled Experiment

Randomization and participant selection.

Randomization is a critical step in ensuring the fairness and validity of a controlled experiment. It involves assigning participants to different experimental conditions in a random and unbiased manner. 

The selection of participants should accurately represent the target population, enhancing the results’ generalizability.

Data Collection Methods and Instruments

Selecting appropriate data collection methods and instruments is pivotal in gathering accurate and relevant data. Researchers often employ surveys, observations, interviews, or specialized tools to record and measure the variables of interest. 

The chosen methods should align with the experiment’s objectives and provide reliable data for analysis.

Monitoring and Maintaining Experimental Conditions

Maintaining consistent and controlled experimental conditions throughout the study is essential. Regular monitoring helps ensure that variables remain constant and uncontaminated, reducing the risk of confounding factors. 

Rigorous monitoring protocols and timely adjustments are crucial for the accuracy and reliability of the experiment.

Analysing Results and Drawing Conclusions

Data analysis techniques.

Data analysis involves employing appropriate statistical and analytical techniques to process the collected data. This step helps derive meaningful insights, identify patterns, and draw valid conclusions. 

Common techniques include regression analysis, t-tests , ANOVA , and more, tailored to the research design and data type .

Interpretation of Results

Interpreting the results entails understanding the statistical outcomes and their implications for the research objectives. 

Researchers analyze patterns, trends, and relationships revealed by the data analysis to infer the experiment’s impact on the variables under study. Clear and accurate interpretation is crucial for deriving actionable insights.

Implications and Potential Applications

Identifying the broader implications and potential applications of the experiment’s results is fundamental. Researchers consider how the findings can inform decision-making, policy development, or further research. 

Understanding the practical implications helps bridge the gap between theoretical insights and real-world application.

Common Challenges and Solutions

Addressing ethical considerations.

Ethical challenges in controlled experiments include ensuring informed consent, protecting participants’ privacy, and minimizing harm. 

Solutions involve thorough ethics reviews, transparent communication with participants, and implementing safeguards to uphold ethical standards throughout the experiment.

Dealing with Sample Size and Statistical Power

The sample size is crucial for achieving statistically significant results. Adequate sample sizes enhance the experiment’s power to detect meaningful effects accurately. 

Statistical power analysis guides researchers in determining the optimal sample size for the experiment, minimizing the risk of type I and II errors .

Mitigating Unforeseen Variables

Unforeseen variables can introduce bias and affect the experiment’s validity. Researchers employ meticulous planning and robust control measures to minimize the impact of unforeseen variables. 

Pre-testing and pilot studies help identify potential confounders, allowing researchers to adapt the experiment accordingly.

A controlled experiment involves meticulous planning, precise execution, and insightful analysis. Adhering to ethical standards, optimizing sample size, and adapting to unforeseen variables are key challenges that require thoughtful solutions. 

Real-world applications showcase the transformative potential of controlled experiments across varied domains, emphasizing their indispensable role in evidence-based decision-making and progress.

• https://www.khanacademy.org/science/biology/intro-to-biology/science-of-biology/a/experiments-and-observations
• https://www.scribbr.com/methodology/controlled-experiment/
• https://link.springer.com/10.1007/978-1-4899-7687-1_891
• http://ai.stanford.edu/~ronnyk/GuideControlledExperiments.pdf
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776925/
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/
• https://www.merriam-webster.com/dictionary/controlled%20experiment

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