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Disadvantages of an independent measure? - Answers

Independent measures design can introduce variability because different participants are used in each condition, which can lead to differences in individual characteristics affecting the results. This variability can make it harder to detect the true effect of the independent variable. Additionally, it often requires a larger sample size to achieve the same statistical power as a repeated measures design, which can increase costs and time for the study. Finally, the need for random assignment to groups is essential, and failure to do so can lead to confounding variables influencing the outcomes.



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Disadvantages of an independent measure? - Answers

https://math.answers.com/math-and-arithmetic/Disadvantages_of_an_independent_measure

Independent measures design can introduce variability because different participants are used in each condition, which can lead to differences in individual characteristics affecting the results. This variability can make it harder to detect the true effect of the independent variable. Additionally, it often requires a larger sample size to achieve the same statistical power as a repeated measures design, which can increase costs and time for the study. Finally, the need for random assignment to groups is essential, and failure to do so can lead to confounding variables influencing the outcomes.



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https://math.answers.com/math-and-arithmetic/Disadvantages_of_an_independent_measure

Disadvantages of an independent measure? - Answers

Independent measures design can introduce variability because different participants are used in each condition, which can lead to differences in individual characteristics affecting the results. This variability can make it harder to detect the true effect of the independent variable. Additionally, it often requires a larger sample size to achieve the same statistical power as a repeated measures design, which can increase costs and time for the study. Finally, the need for random assignment to groups is essential, and failure to do so can lead to confounding variables influencing the outcomes.

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      Independent measures design can introduce variability because different participants are used in each condition, which can lead to differences in individual characteristics affecting the results. This variability can make it harder to detect the true effect of the independent variable. Additionally, it often requires a larger sample size to achieve the same statistical power as a repeated measures design, which can increase costs and time for the study. Finally, the need for random assignment to groups is essential, and failure to do so can lead to confounding variables influencing the outcomes.

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