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Extraneous variables are factors other than the independent variable that can influence the dependent variable, potentially skewing the results of an experiment. Confounding variables are a specific type of extraneous variable that is related to both the independent and dependent variables, making it difficult to determine the true effect of the independent variable on the dependent variable. Both types of variables can threaten the internal validity of a study if not properly controlled.
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What is the difference between moderating and extraneous variables?
Extraneous variable a.k.a. Confounding vaiable is a variable that affects an independent variable n also afects a dependent variable at d same time confounding relatnship btn the independent and dependent variable. Mediating variable a.k.a. Intervening variable, it is a variable forming a link btn two variables that are causualy conected.
What is an example of a confounding variable?
A confounding variable is an extraneous factor that can influence both the independent and dependent variables in a study, potentially skewing the results. For example, in a study examining the relationship between exercise and weight loss, diet could be a confounding variable, as it impacts both the amount of weight lost and the effectiveness of exercise. If not controlled for, diet may lead to incorrect conclusions about the impact of exercise on weight loss.
What are examples of extraneous variables?
ask your hand
What are Confounding Variables?
In any experiment there are many kinds of variables that will effect the experiment. The independent variable is the manipulation for the experiment and the dependent variable is the measure you take from that experiment. Confounding variables are things in which have an effect on the dependent variable, but were taken into account in the experimental design. For example, you want to know if Drug X has an effect on causing sleep. The experimenter must take care to design the experiment so that he can be very sure that the subjects in the study fell asleep because of the influence of his Drug X, and that the sleepiness was not caused by other factors. Those other factors would be confounding variables.
What is meant by confounding?
Confounding refers to a situation in research where an outside variable influences both the independent and dependent variables, leading to a misleading association between them. This can obscure the true relationship being studied, making it difficult to determine causality. Confounding variables must be controlled or accounted for to ensure accurate interpretations of research findings.
What is the difference between moderating and extraneous variables?
Extraneous variable a.k.a. Confounding vaiable is a variable that affects an independent variable n also afects a dependent variable at d same time confounding relatnship btn the independent and dependent variable. Mediating variable a.k.a. Intervening variable, it is a variable forming a link btn two variables that are causualy conected.
What are the 4 extraneous variables?
Extraneous variables are factors other than the independent variable that can influence the dependent variable, potentially skewing results. The four common types of extraneous variables include: Participant variables (individual differences between subjects, such as age or intelligence) Situational variables (environmental factors like temperature or time of day) Measurement variables (inconsistencies in how data is collected or measured) Confounding variables (factors that are related to both the independent and dependent variables, leading to false conclusions). Controlling these variables is crucial for ensuring the validity of research findings.
Can extraneous variables be controlled?
no the variables cant be controlled.
Why is it important to identify confounding variables in your experiment?
Identifying confounding variables is crucial in an experiment because they can obscure the true relationship between the independent and dependent variables. If not controlled, these extraneous factors may lead to inaccurate conclusions, suggesting that a treatment or intervention has an effect when it does not, or vice versa. By recognizing and addressing confounders, researchers enhance the validity and reliability of their findings, ensuring that the results genuinely reflect the phenomenon under investigation. Ultimately, this strengthens the overall credibility of the research.
What are some way to control extraneous variables?
Extraneous variables can be controlled through various methods, including random assignment, which ensures that participants are evenly distributed across different groups, minimizing bias. Standardizing procedures, such as maintaining consistent environments and instructions for all participants, helps reduce variability. Additionally, researchers can use control groups to compare results and statistical techniques to account for potential confounding factors. Lastly, pre-screening participants to match them on key characteristics can also help mitigate the influence of extraneous variables.
What is an example of a confounding variable?
A confounding variable is an extraneous factor that can influence both the independent and dependent variables in a study, potentially skewing the results. For example, in a study examining the relationship between exercise and weight loss, diet could be a confounding variable, as it impacts both the amount of weight lost and the effectiveness of exercise. If not controlled for, diet may lead to incorrect conclusions about the impact of exercise on weight loss.
What variables did you have to control in order to get a valid result?
We controlled the independent variable (the variable we manipulated) to observe its effect on the dependent variable (the variable we measured). We also controlled for any potential confounding variables that could influence the results. Additionally, we ensured consistency in experimental conditions to eliminate any extraneous variables that could impact the outcome.
What are examples of extraneous variables?
ask your hand
What are the three variables that play an important role in a Practical Investigation?
Independent Variables, Dependent Variables and Extraneous Variables.
What are Confounding Variables?
In any experiment there are many kinds of variables that will effect the experiment. The independent variable is the manipulation for the experiment and the dependent variable is the measure you take from that experiment. Confounding variables are things in which have an effect on the dependent variable, but were taken into account in the experimental design. For example, you want to know if Drug X has an effect on causing sleep. The experimenter must take care to design the experiment so that he can be very sure that the subjects in the study fell asleep because of the influence of his Drug X, and that the sleepiness was not caused by other factors. Those other factors would be confounding variables.
What is Situation-Relevant Confounding Variable?
A situation-relevant confounding variable is a third variable that is related to both the independent and dependent variables being studied, which can lead to a spurious relationship between them. It is crucial to identify and control for situation-relevant confounding variables in research to ensure that the true relationship between the variables of interest is accurately captured.
How can you eliminate confounding variables in your experiment?
To eliminate confounding variables, or variables that were not controlled and damaged the validity of the experiment by affecting the dependent and independent variable, the experimenter should plan ahead. They should run many checks before actually running an experiment.
