Internal Validity: The degree to which a study can rule out alternative explanations for the results and thus support a causal relationship between the independent and dependent variables.
Key Concepts
Independent Variable (IV): The variable manipulated by the experimenter.
Dependent Variable (DV): The variable measured or affected in the experiment.
Confounding Variables: Variables other than the IV that may affect the DV.
Experiment Example
Scenario: Scientists investigate the impact of drinking water on lifespan.
Method: Subjects are given water and left in a room; revisited after 80 years.
Findings: All subjects died, leading to an incorrect conclusion that water is deadly.
Issues with the Experiment
Confounding Variables: Locking people in a room without food impacts lifespan, not just the water.
Poor Internal Validity: Numerous factors, aside from the IV, influenced DV.
Improving Internal Validity
Control Group: Essential for comparing results and ruling out confounding variables.
Example: A control group locked in the room without water might face the same fate, highlighting issues other than water intake.
Assessment of Experiments
Always ensure a control group is present.
Control group should experience the same conditions, minus the IV/test intervention.
Comparing experimental and control groups helps evaluate the internal validity of the study.