Alternation between a cantor chanting psalm verses and a choir singing a refrain is called:
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A standardized variable is, in terms of scientific experimentation, more commonly referred to as a control or constant variable.
<em>Though I was unable to locate the full question in order to provide an answer specific to this question, allow me to provide a general overview of the role each variable plays within an experiment, thus allowing you to use this information towards your specific experiment. </em>
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In order to perform a successful experiment, we can identify at least three kinds of variables, these are:
- Independent variable
- dependent variable
- Control variable
In an experiment, the Independent variable is one whose value does not depend on the others. What this means is that this variable will<u> not react to changes that occur in others</u>. One example of this can be the <em>color of light</em> in an experiment to test <em>how colored light affects plant growth</em>. We know this is the independent variable here because the color of the light is not affected by the species of plant, type of soil, or any other variable present.
The dependent variable in an experiment is just the opposite, it is, as the name implies, a variable whose value<u> depends on the other variables present</u>. In any experiment, this variable represents<u> the data that we seek to measure.</u> For the example given above, it would correspond to the growth of the plants.
Finally, the last variable we must identify is that of the control variable, also known as the constant or standardized variable. This variable is of vital importance for the accuracy of any experiment. This variable corresponds <u>to those factors which we maintain </u><u>constant </u><u>through each trial in the experiment,</u> for the example above, keeping the kind of soil or species of plant constant through each test.
This is done in order to minimize the factors that may affect the outcome of the experiment, and this way, in the presence of any change, we can attribute that change to the correct factor that caused it.
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