BHS Methods in Behavioral Sciences I April 9, 2003 Chapter 2 (Stanovich) – Falsifiability: How to Foil Little Green Men in the Head

Logic of Experimentation  Two forms of logic: Deduction – moving from general principles to specific conclusions. Induction – moving from specific observations to general principles.  Induction is used during naturalistic and exploratory research.  Deduction is used during experiments.

Propositional Logic  Modus Ponens (confirmatory) If p then q Observe p Conclude q  Modus Tollens (disconfirmatory) If p then q Observe not-q Conclude not-p

Logical Fallacies  Affirming the consequent If p then q Observe q Conclude p  Denying the antecedent If p then q Observe not-p Conclude not-q

Falsifiability  Seeking support for hypotheses commits the logical fallacy of affirming the consequent.  Instead, we must test hypotheses by seeking disconfirmatory evidence.  A testable theory is one that can be proven wrong – if it is wrong. It must have the chance to fail. A theory cannot explain every outcome.

Popper’s Approach  Predictions from theory (hypotheses) must be specific. They must state what will happen and what will not happen. General predictions or all-encompassing predictions cannot be tested (are unfalsifiable).  When data accumulates that contradicts theory, then theory must be changed. Data is not thrown out – explanations are.

Two Hypotheses  Null hypothesis (H 0 ): There will be no difference between treatment and control groups (no treatment effect).  Alternative hypothesis (H 1 ): There will be a difference of a particular kind. Directionality – states how the treatment group will differ from the control group.  We test the null hypothesis and by rejecting it (disconfirming it) can accept the alternative.

The Neyman-Pearson Approach  Two theories can be compared by predicting incompatible outcomes: If theory A is correct, hypothesis A will be confirmed and B will be disconfirmed. If theory B is correct, hypothesis B will be confirmed and A will be disconfirmed.  The comparison is not with the control group ( is there a treatment effect or not) but with the predictions made by the two theories.

Errors are Important  We learn something, even when an experiment does not “work” – does not produce the expected result. Knowledge advances when we find that our ideas are wrong and can abandon incorrect beliefs. We must be willing to let evidence guide belief – not the other way around.  Scientists criticize each other’s ideas in an ongoing dialectic that produces change.

Working on the Fringes  Interesting questions are those that: Exist at the fringes of knowledge. Can be tested using existing methods.  Many questions are important but untestable.  Some questions are interesting to the public but not to scientists because they have already been answered: ESP and other paranormal claims, astrology.