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There cannot be one since the answer depends on the form in which the effect is measured: whether the effect is qualitative or quantitative.

There are various non-parametric measures of correlation or concordance. For data that are more quantitative there are more powerful tests such as the F-test for independent Normal distributions.

Q: What serves as a standard of comparison to evaluate the effect of the independent variables on the dependent variable?

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In statistics, the standard of comparison is the r2 which is a percentage that explains what percentage of the dependent variable can be accounted for by the independent variable.

The correlation coefficient, plus graphical methods to verify the validity of a linear relationship (which is what the correlation coefficient measures), and the appropriate tests of the statisitical significance of the correlation coefficient.

There cannot be one since the answer depends on the form in which the effect is measured: whether the effect is qualitative or quantitative. There are various non-parametric measures of correlation or concordance. For data that are more quantitative there are more powerful tests such as the F-test for independent Normal distributions.

There cannot be one since the answer depends on the form in which the effect is measured: whether the effect is qualitative or quantitative. There are various non-parametric measures of correlation or concordance. For data that are more quantitative there are more powerful tests such as the F-test for independent Normal distributions.

There cannot be one since the answer depends on the form in which the effect is measured: whether the effect is qualitative or quantitative. There are various non-parametric measures of correlation or concordance. For data that are more quantitative there are more powerful tests such as the F-test for independent Normal distributions.

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In statistics, the standard of comparison is the r2 which is a percentage that explains what percentage of the dependent variable can be accounted for by the independent variable.

The control serves as the standard in a science experiment.

ControlThe answer will depend on the nature of the effect. IFseveral requirements are met (the effect is linear, the "errors" are independent and have the same variance across the set of values that the independent variable can take (homoscedasticity) then, and only then, a linear regression is a standard. All to often people use regression when the data do not warrant its use.

The correlation coefficient, plus graphical methods to verify the validity of a linear relationship (which is what the correlation coefficient measures), and the appropriate tests of the statisitical significance of the correlation coefficient.

The control group serves as a standard of comparison to evaluate the effect of the independent variable on the dependent variable. By comparing the results of the experimental group receiving the independent variable with the control group, researchers can isolate the effect of the independent variable on the dependent variable.