Experimental design, validity, and basic statistical concepts used in psychological research methods courses.
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- What is an independent variable?
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The variable manipulated by the researcher to observe its effect on the dependent variable.- What is a dependent variable?
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The outcome variable measured in an experiment to assess the effect of the independent variable.- Define random assignment.
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The process of randomly placing participants into groups to ensure groups are equivalent at the start of a study.- What is a control group?
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The group that does not receive the experimental treatment and is used as a baseline for comparison.- Define internal validity.
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The degree to which a study establishes that an independent variable caused the observed effect on the dependent variable.- Define external validity.
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The extent to which research findings can be generalized to other populations, settings, and times beyond the study.- Define construct validity.
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The extent to which a test accurately measures the theoretical construct it claims to measure.- Define statistical validity.
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The correctness of statistical conclusions about whether a relationship between variables actually exists in the population.- What is a confounding variable?
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A variable other than the independent variable that affects the dependent variable and obscures the true relationship.- What is an operational definition?
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A precise description of how a variable will be measured or manipulated in a specific study.- What is the difference between reliability and validity?
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Reliability is consistency of measurement; validity is whether a measure actually assesses what it claims to measure.- What is a null hypothesis?
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The statistical hypothesis that assumes no relationship or difference exists between variables or groups.- What is an alternative hypothesis?
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The research hypothesis proposing that a specific relationship or difference exists between variables or groups.- Define a Type I error.
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Rejecting the null hypothesis when it is actually true, also called a false positive.- Define a Type II error.
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Failing to reject the null hypothesis when it is actually false, also called a false negative.
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