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What serves as a standard of comparison to evaluate the effect of the independent variables on the dependent variable?
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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What serves as a standard of comparison to evaluate the effectof the independent variableon the dependent variable?
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.
What serves as a standard of comparison to evaluate the effect of the independent variable on the dependet variable?
The standard of comparison used to evaluate the effect of the independent variable on the dependent variable is typically the control group. This group does not receive the experimental treatment or manipulation, allowing researchers to observe the natural outcomes without the influence of the independent variable. By comparing the results of the experimental group to the control group, researchers can determine the effect of the independent variable more accurately.
What serves as standard of comparison to evaluate effect of the independent variable on dependent 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.
What serves as a standard of comparison to evaluate the effect of the independent variable on the dependent?
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.
What serves as a standard of comparison to evaluate the effect to the independent variable of the dependent variable?
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.
What serves as a standard of comparison to evaluate the effectof the independent variableon the dependent variable?
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.
What serves as a standard of comparison to evaluate the effectof the independent variable on the dependent variable?
The control serves as the standard in a science experiment.
What serves as a standard of comparison to evaluate the effect of the dependent variable on the dependent variable?
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.
What serves as standard of comparison to evaluate effect of the independent variable on dependent 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.
What serves as a standard of comparison to evaluate the effect of the independent variable on the dependent variable?
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.
What as a standard of comparison to evaluate the effect of the independent variable on the dependent variable?
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.
What serves as a comparison to evaluate the effect of the the independent variable on the dependent variable?
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.
What serves as a standard of comparison to evaluate the effect of the independent variable on the dependent?
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.
What serve as a standard of comparison to evaluate the effects of the independent variable on the dependent variable?
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.
What serves as a standard of comparison to evaluate the effect of the independent variable on the dependent variable.?
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.
What serves as a standard of comparison to evaluate the effect to the independent variable of the dependent variable?
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.
What serves as a standard of comparison to evaluate the effect of the independent variable on the the dependent variable?
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.
