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BHS 204-01 Methods in Behavioral Sciences I

This chapter explores two forms of logic, deduction and induction, in the context of behavioral sciences. It discusses propositional logic, logical fallacies, and the concept of falsifiability. The approaches of Popper and Neyman-Pearson are examined, highlighting the importance of errors and the need for evidence-based beliefs. The chapter also emphasizes the value of working on the fringes of knowledge and the limitations of untestable questions.

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BHS 204-01 Methods in Behavioral Sciences I

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  1. BHS 204-01Methods in Behavioral Sciences I April 9, 2003 Chapter 2 (Stanovich) – Falsifiability: How to Foil Little Green Men in the Head

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. Two Hypotheses • Null hypothesis (H0): • There will be no difference between treatment and control groups (no treatment effect). • Alternative hypothesis (H1): • 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.

  8. 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.

  9. 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.

  10. 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.

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