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