The experiment
Definition and Purpose of the Experiment
Not trial-and-error tinkering; it's a logical, step-by-step method to test cause-effect relationships.
Based on syllogistic reasoning: two premises (P1, P2) yield an inevitable conclusion C. Notation: (P1 \land P2) \rightarrow C
The Logical Foundation
Two premises, the conclusion follows if both premises are true.
Formal form: (P1 \land P2) \rightarrow C
Where
P_1: Groups treated identically as possible
P_2: Exactly one difference introduced
C: Observed difference is due to the introduced difference
Experimental Design Essentials
Treat two groups as identically as possible
Introduce one and only one difference between the groups
Keep other conditions identical and controlled
If groups differ on the outcome, the difference is due to the single manipulated variable
Why Observational Methods Fail for Causation
Real-world observations have many confounds; cannot establish causation
Example: naturalistic observation of alcohol and aggression may show association but not causation due to other factors
Multiple plausible explanations exist; cannot identify the true cause without isolation
How the Logic Supports Causal Inference
By isolating the effect of one variable and holding others constant
If the two groups differ on the outcome, reference to the one manipulated variable is the causal explanation
Practical Steps in an Experiment
Step 1: Treat two groups as identically as possible
Step 2: Introduce one and only one difference between them
Step 3: Observe the outcome; if there is a difference, attribute it to the manipulated difference
Summary and Key Takeaways
Experiments verify cause-effect relationships and support hypothesis testing
Observational methods alone are insufficient for causal claims
Controlled laboratory design is essential to isolate variables and infer causation
Preview of Next Video
We will examine an experimental design example, data collection, analysis, and potential pitfalls.