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Loren Booda
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Would you agree that statistics can be mathematically misrepresented to prove most related arguments both true and false?
Can statistics be manipulated to support both true and false arguments?
- Context: Undergrad
- Thread starter Loren Booda
- Start date
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- Statistics
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Discussion Overview
The discussion revolves around the manipulation of statistics and whether they can be misrepresented to support both true and false arguments. Participants explore the implications of data mining, the integrity of statistical models, and the general public's understanding of statistics.
Discussion Character
- Debate/contested
- Conceptual clarification
- Technical explanation
Main Points Raised
- Some participants assert that statistics can be mathematically misrepresented to support various arguments, both true and false.
- Data mining is mentioned as a method that allows for any statistical result to be achieved.
- One participant questions the meaning of "misrepresented," suggesting that while lies can be used to prove a point, that may not align with the intended meaning of the term.
- Another participant emphasizes that proper statistical models depend on strict application of techniques and assumptions, noting that misuse is common due to a general lack of understanding among the public.
- A similar point is reiterated by another participant, highlighting that while statistics can be misrepresented, the underlying mathematics remains accurate.
- One participant agrees that statistics can be used dishonestly in a way that may be accepted by those not well-versed in statistics, but expresses uncertainty about whether this is always the case.
Areas of Agreement / Disagreement
Participants express differing views on the nature of statistical misrepresentation and its implications. There is no consensus on the extent to which statistics can be manipulated or the definitions of misrepresentation.
Contextual Notes
Participants highlight the complexity of statistical interpretation and the potential for misuse, but do not resolve the nuances of what constitutes misrepresentation or the conditions under which it occurs.