How is a within-subjects design a solution to the problem of increase in error variance/extraneous subject variables?
Answer: Because participants are experiencing all levels of the IV, it is easier to detect differences between the conditions.
The characteristics each person is bringing into the experiment is going to be consistent across all the levels of IV.
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Principles of Experimental Design
- How do you solve the problem of 'order effects' in a within-subjects design?
- If an extraneous variable is causing differences between groups, what would this be called?
- What could cause a third unknown factor influencing you're results?
- Which type of experiment does not allow you to explain the results?
- Which type of experiment allows you to explain and predict you're results?
- What is counterbalancing?
- What is a practice effect?
- What is an 'order effect'?
- Why is it that between subjects design may have an increase in error variance?
- What is the difficulty when it comes to an increase in error variance in between-subjects design?
- What does participant variability lead to in between subjects design?
- What is a way in stopping the 'order effect' within a within-subjects design?
- What is a problem with a within-subject design?
- What is the benefit of a within-subjects design?
- What is a within-subjects design?
- Does random assignment and matching eliminate confounding variables?
- What could be a problem in making subject variables a control variable?
- What is another way to control for extraneous subject variables that have potential to become confounds?
- What is a confounding variable?
- What is matching?
- What is another way to prevent extraneous subject variables becoming confounds?
- How do you control for subject variables that may become a confound?
- How might subject variables (height, gender, age, weight) in a between subjects design become a confound?
- What is a between subjects design?