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General Tabletop Discussion
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A discussion of metagame concepts in game design
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<blockquote data-quote="Ovinomancer" data-source="post: 7473430" data-attributes="member: 16814"><p>I use stats in my day job for science reasons. I do it because it creates a predictable model with great skill to do radio frequency work. However, the stats I use aren't reality, they're just a good tool, one that has shown repeated reliability for decades for this kind of work. I don't confuse statistics as being the useful part of this tool -- this tool stands on it's own merits, and statistics doesn't inherent any good faith from me from this one (actually a family) of tool. </p><p></p><p>Stats builds a model. The old saw, "All models are wrong; some are useful," is true. There are many useful tools in stats, but they require the user to be aware of their limitations, use clean data, and understand what the model actually says. Whenever someone says 'statistics prove it' I cringe. This is fundamentally incorrect statement. Stats aren't run on the data, they're run on parameters of the data, and those parameters are all assumptions the user is making. The math then works, and spits out an answer, and the user is now in the easy position of thinking that answer is based on the data rather than the parameterization. The answer is also very often precise -- perhaps a wee p-value is obtained. This leads to overconfidence in the result. In short, it's very easy to both lie to yourself (and others) with stats and to also be overconfident in your results.</p><p></p><p>This doesn't mean statistics isn't useful -- I make a comfortable living uses statistical approaches in my job. But, most often, stats are just guesses cloaked in the justifying garb of numbers. I have a generally negative view of statistics due to how often it's misused. I can be very favorable of specific statistical models, given they have shown to have good skill and don't mistake themselves for truth.</p><p></p><p>So, yes, under that understanding I know that statistics can be useful for discovery (correlations only) and can provide some support to a theory. They cannot ever <em>prove </em>a theory, though.</p></blockquote><p></p>
[QUOTE="Ovinomancer, post: 7473430, member: 16814"] I use stats in my day job for science reasons. I do it because it creates a predictable model with great skill to do radio frequency work. However, the stats I use aren't reality, they're just a good tool, one that has shown repeated reliability for decades for this kind of work. I don't confuse statistics as being the useful part of this tool -- this tool stands on it's own merits, and statistics doesn't inherent any good faith from me from this one (actually a family) of tool. Stats builds a model. The old saw, "All models are wrong; some are useful," is true. There are many useful tools in stats, but they require the user to be aware of their limitations, use clean data, and understand what the model actually says. Whenever someone says 'statistics prove it' I cringe. This is fundamentally incorrect statement. Stats aren't run on the data, they're run on parameters of the data, and those parameters are all assumptions the user is making. The math then works, and spits out an answer, and the user is now in the easy position of thinking that answer is based on the data rather than the parameterization. The answer is also very often precise -- perhaps a wee p-value is obtained. This leads to overconfidence in the result. In short, it's very easy to both lie to yourself (and others) with stats and to also be overconfident in your results. This doesn't mean statistics isn't useful -- I make a comfortable living uses statistical approaches in my job. But, most often, stats are just guesses cloaked in the justifying garb of numbers. I have a generally negative view of statistics due to how often it's misused. I can be very favorable of specific statistical models, given they have shown to have good skill and don't mistake themselves for truth. So, yes, under that understanding I know that statistics can be useful for discovery (correlations only) and can provide some support to a theory. They cannot ever [I]prove [/I]a theory, though. [/QUOTE]
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