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Module 7: Fact or Fallacy?

Quick questions on Logical fallacies and cognitive bias: HSC Investigating Science Module 7

15short Q&A pairs drawn directly from our worked dot-point answer. For full context and worked exam questions, read the parent dot-point page.

What is common logical fallacies?
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Ad hominem. Attacking the person rather than their argument.
What is common cognitive biases?
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Confirmation bias. Seeking and remembering information that confirms existing beliefs while ignoring contrary evidence. The most pervasive cognitive bias in scientific reasoning.
What is how biases distort science?
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Hypothesis formation. Confirmation bias narrows the questions asked.
What is a specific Australian example?
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The H. pylori case (Module 5). For decades the medical consensus held that stress and acid caused peptic ulcers. Doctors dismissed the bacterial hypothesis as implausible (an instance of consensus bias and ad hominem dismissal of Barry Marshall's outsider status). Marshall countered with self-experimentation, eventually winning the 2005 Nobel Prize.
What is ad hominem?
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Attacking the person rather than their argument.
What is appeal to authority?
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Accepting a claim because an authority figure said it, without evidence.
What is false dichotomy?
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Presenting only two options when more exist.
What is post hoc ergo propter hoc?
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"After this, therefore because of this." Treating temporal sequence as causal.
What is strawman?
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Attacking a misrepresented version of an opponent's argument.
What is slippery slope?
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Claiming one step inevitably leads to extreme consequences without evidence.
What is naturalistic fallacy?
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Treating natural as good.
What is genetic fallacy?
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Judging a claim by its origin rather than its merits.
What is argument from ignorance?
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Treating absence of evidence as evidence of absence (or presence).
What is confirmation bias?
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Seeking and remembering information that confirms existing beliefs while ignoring contrary evidence. The most pervasive cognitive bias in scientific reasoning.
What is anchoring?
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Over-weighting the first piece of information encountered. The initial estimate biases subsequent judgements.

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