Misleading statistic : often , an argument will rely on numbers/data to support a conclusion. Stats may appear important, but can be used in misleading ways.

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1. Size of sample

Ensure the study has enough participants

If the size of the sample is too small, even if unbiased, it is rejectable

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2. Date of sample

Make sure the date of the sample is recent to be relevant

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3. Unreliable statistics

If a pole is taken but individuals may not answer honestly, the stats may be untrustworthy

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4. Confusing use of the averages

Ex. If you know the average salary in Quebec is 45k, this does not mean the average salary in Longueil is above 40k

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5. Proving one thing, Concluding Another

Don't draw conclusions your data cant support

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6. Biased Sample

This biased set is “unrepresentative” of the whole

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7. Deceiving by omitting information

“Bob must be a great philosophy teacher as his student dropout rate was 50% less than other teachers in his school last semester”

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Assumptions

An assumption is a premise without justification.

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Explicit assumption

An assumption that is stated within an argument and just “assumed” to be acceptable. They are unstated and unjustified.

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Implicit/Assumption

A premise that is unstated but really is needed for the conclusion to follow from the stated premises

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