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Confounding variables are variables that aren't accounted for that may affect the outcome of an experiment. For example, they are things you don't expect to be affecting something. Say we are doing any experiment, and we have set it up to test variables X and Y. However, at the end of the experiment, we find that another variable (variable Z) was part of the experiment but we didn't plan on it being there in the first place. Basically, you need to set it up so that no other variables outside of the ones you want to take place are in the experiment.
the only variables in an experiment are the independent variables [the thing in an experiment your going to change. and the dependent variables [the thing in an experiment your going to measure.
Independant variables
Independant variables
An experiment in which all variables stay the same is called a "controlled 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.
Confounding variables in the Stanford prison experiment could include the psychological characteristics of the participants, such as pre-existing attitudes towards authority or aggression. Additionally, the specific conditions in which the experiment took place, such as the lack of oversight and the power dynamics between the guards and prisoners, could also be considered confounding variables that influenced the outcomes of the study.
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.
Confounding variables are variables that aren't accounted for that may affect the outcome of an experiment. For example, they are things you don't expect to be affecting something. Say we are doing any experiment, and we have set it up to test variables X and Y. However, at the end of the experiment, we find that another variable (variable Z) was part of the experiment but we didn't plan on it being there in the first place. Basically, you need to set it up so that no other variables outside of the ones you want to take place are in the experiment.
Yes, you should always be sterile before performing any experiment as to not add any variables.
Internal validity is higher when you stop confounding variables interfering with the experiment (things that effect the results). Internal validity occurs when a researcher controls all confounding variables and the only variable influencing the results of a study is the one being manipulated by the researcher. This means that the variable the researcher intended to study is indeed the one affecting the results and not something else.
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Variables that do not change in an experiment are independent variables.
Variables that do not change in an experiment are independent variables.
the only variables in an experiment are the independent variables [the thing in an experiment your going to change. and the dependent variables [the thing in an experiment your going to measure.
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independent variables :):):):):):):):):):):):)