One approach is to measure them in the same order for all participants—usually with the most important one first so that it cannot be affected by measuring the others. Another approach is to counterbalance, or systematically vary, the order in which the dependent variables are measured.
When the independent variable is a construct that can only be manipulated indirectly—such as emotions and other internal states—an additional measure of that independent variable is often included as a manipulation check. This is done to confirm that the independent variable was, in fact, successfully manipulated. For example, Schnall and her colleagues had their participants rate their level of disgust to be sure that those in the messy room actually felt more disgusted than those in the clean room.
Manipulation checks are usually done at the end of the procedure to be sure that the effect of the manipulation lasted throughout the entire procedure and to avoid calling unnecessary attention to the manipulation. Manipulation checks become especially important when the manipulation of the independent variable turns out to have no effect on the dependent variable.
Imagine, for example, that you exposed participants to happy or sad movie music—intending to put them in happy or sad moods—but you found that this had no effect on the number of happy or sad childhood events they recalled. This could be because being in a happy or sad mood has no effect on memories for childhood events. But it could also be that the music was ineffective at putting participants in happy or sad moods.
Another common approach to including multiple dependent variables is to operationally define and measure the same construct, or closely related ones, in different ways.
Imagine, for example, that a researcher conducts an experiment on the effect of daily exercise on stress. The dependent variable, stress, is a construct that can be operationally defined in different ways.
For this reason, the researcher might have participants complete the paper-and-pencil Perceived Stress Scale and measure their levels of the stress hormone cortisol.
This is an example of the use of converging operations. If the researcher finds that the different measures are affected by exercise in the same way, then he or she can be confident in the conclusion that exercise affects the more general construct of stress.
When multiple dependent variables are different measures of the same construct—especially if they are measured on the same scale—researchers have the option of combining them into a single measure of that construct. You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.
Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.
Scientists and researchers must always adhere to a certain code of conduct when collecting data from others. These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.
Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe. Both are important ethical considerations. You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.
You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.
Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure. Want to contact us directly? No problem.
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Home Frequently asked questions Can I include more than one independent or dependent variable in a study? Can I include more than one independent or dependent variable in a study? What is sampling? Reliability and validity are both about how well a method measures something: Reliability refers to the consistency of a measure whether the results can be reproduced under the same conditions.
Validity refers to the accuracy of a measure whether the results really do represent what they are supposed to measure. What is the difference between internal and external validity?
What is experimental design? 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.
What are independent and dependent variables? For example, in an experiment about the effect of nutrients on crop growth: The independent variable is the amount of nutrients added to the crop field. The dependent variable is the biomass of the crops at harvest time. What is the difference between quantitative and categorical variables?
What is the difference between discrete and continuous variables? Discrete and continuous variables are two types of quantitative variables : Discrete variables represent counts e. Continuous variables represent measurable amounts e. What is a confounding variable? How do I decide which research methods to use? If you want to measure something or test a hypothesis , use quantitative methods.
If you want to explore ideas, thoughts and meanings, use qualitative methods. If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods. What is mixed methods research? What is internal validity? What are threats to internal validity? What is the difference between a longitudinal study and a cross-sectional study? What are the pros and cons of a longitudinal study? What is an example of a longitudinal study?
How long is a longitudinal study? Why do a cross-sectional study? What are the disadvantages of a cross-sectional study? What is external validity? What are the two types of external validity? What are threats to external validity? Why are samples used in research? When are populations used in research?
What is sampling error? What is sampling bias? Why is sampling bias important? What are some types of sampling bias? How do you avoid sampling bias? What is probability sampling? What is non-probability sampling? Why are independent and dependent variables important? What is an example of an independent and a dependent variable? The type of soda — diet or regular — is the independent variable.
The level of blood sugar that you measure is the dependent variable — it changes depending on the type of soda. Can a variable be both independent and dependent?
Why do confounding variables matter for my research? What is the difference between confounding variables, independent variables and dependent variables? How do I prevent confounding variables from interfering with my research? What is data collection?
What are the benefits of collecting data? When conducting research, collecting original data has significant advantages: You can tailor data collection to your specific research aims e.
What is operationalization? What is hypothesis testing? What are the main qualitative research approaches? There are five common approaches to qualitative research : Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organization to understand its culture. Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions. Action research links theory and practice in several cycles to drive innovative changes. How do you analyze qualitative data? There are various approaches to qualitative data analysis , but they all share five steps in common: Prepare and organize your data.
Review and explore your data. Develop a data coding system. Assign codes to the data. Identify recurring themes. What is a Likert scale? Are Likert scales ordinal or interval scales?
What is the difference between a control group and an experimental group? Do experiments always need a control group? What is blinding? What is the difference between single-blind, double-blind and triple-blind studies? In a single-blind study , only the participants are blinded. In a double-blind study , both participants and experimenters are blinded. In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.
Why is blinding important? What is a quasi-experiment? When should I use a quasi-experimental design? What is simple random sampling? What is an example of simple random sampling? When should I use simple random sampling? However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied, If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.
What is cluster sampling? The clusters should ideally each be mini-representations of the population as a whole. What are the types of cluster sampling? In single-stage sampling , you collect data from every unit within the selected clusters.
In double-stage sampling , you select a random sample of units from within the clusters. In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.
What are some advantages and disadvantages of cluster sampling? What is stratified sampling? When should I use stratified sampling? Can I stratify by multiple characteristics at once? What is systematic sampling? How do I perform systematic sampling? There are three key steps in systematic sampling : Define and list your population , ensuring that it is not ordered in a cyclical or periodic order. Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
Choose every k th member of the population as your sample. How can you tell if something is a mediator? Why should you include mediators and moderators in a study? What is a control variable? Why are control variables important? What is random assignment? How do you randomly assign participants to groups? When do you use random assignment? Can you use a between- and within-subjects design in the same study?
What are the pros and cons of a between-subjects design? Advantages: Prevents carryover effects of learning and fatigue.
Shorter study duration. Disadvantages: Needs larger samples for high power. Uses more resources to recruit participants, administer sessions, cover costs, etc. Individual differences may be an alternative explanation for results. What are the pros and cons of a within-subjects design? Advantages: Only requires small samples, Statistically powerful, Removes the effects of individual differences on the outcomes. Disadvantages: Internal validity threats reduce the likelihood of establishing a direct relationship between variables, Time-related effects, such as growth, can influence the outcomes, Carryover effects mean that the specific order of different treatments affect the outcomes.
What is a factorial design? What are the types of extraneous variables? Experimenter effects : unintentional actions by researchers that influence study outcomes. What are the requirements for a controlled experiment? Grade Levels. Physical Science. Earth and Environmental Science. Behavioral and Social Science. What are Variables? What is an Independent Variable? What is a Dependent Variable? What is a Control Variable? Teacher Tool Box. Water faucet opening closed, half open, fully open Amount of water flowing, measured in liters per minute The faucet Water pressure, or how much the water is "pushing" "Different water pressure might also cause different amounts of water to flow and different faucets may behave differently, so to ensure a fair test, I want to keep the water pressure and the faucet the same for each faucet opening that I test.
Temperature of the water measured in degrees Celsius Amount of sugar that dissolves completely, measured in grams Stirring Type of sugar "More stirring might also increase the amount of sugar that dissolves, and different sugars might dissolve in different amounts, so to ensure a fair test I want to keep these variables the same for each cup of water.
Amount of fertilizer, measured in grams Growth of the plant, measured by its height Growth of the plant, measured by the number of leaves See Measuring Plant Growth for more ways to measure plant growth. Same type of fertilizer Same pot size for each plant Same plant type in each pot Same type and amount of soil in each pot Same amount of water and light Make measurements of growth for each plant at the same time "The many variables above can each change how fast a plant grows, so to ensure a fair test of the fertilizer, each of them must be kept the same for every pot.
Voltage of the electricity, measured in volts Speed of rotation, measured in revolutions per minute RPMs Same motor for every test The motor should be doing the same work for each test turning the same wheel, propeller, or whatever "The work that a motor performs has a big impact on its speed, so to ensure a fair test, I must keep that variable the same.
Time measured, in minutes Height of candle, measured in centimeters, at regular intervals of time for example, every 5 minutes Use same type of candle for every test Wind—make sure there is none.
Groups receiving the survey: Teenagers or parents Amount of time that each person listens to music per day, measured in hours Ask the question in exactly the same way to each individual. Teacher location: The teacher is either in the room or not in the room.
Fenders: The bicycle either has fenders or it does not "Many engineering projects have alternative designs with independent variables like this one with and without fenders. Riding at the same speed Same size and depth of puddle. Sample Here is a sample containing the variables and hypothesis. Explore Our Science Videos. Lesson Plan Introduction. The faucet Water pressure, or how much the water is "pushing" "Different water pressure might also cause different amounts of water to flow and different faucets may behave differently, so to ensure a fair test, I want to keep the water pressure and the faucet the same for each faucet opening that I test.
Stirring Type of sugar "More stirring might also increase the amount of sugar that dissolves, and different sugars might dissolve in different amounts, so to ensure a fair test I want to keep these variables the same for each cup of water. Growth of the plant, measured by its height Growth of the plant, measured by the number of leaves See Measuring Plant Growth for more ways to measure plant growth.
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