Dak Posted September 25, 2008 Posted September 25, 2008 basic question: 1/ on day one, 45% of people are in favour of x 2/ on day two, 50% of people are in favour of x assume a margin of error of [math]{\pm}[/math]0% and a certainty of 95% (i.e., 5% chance of each statement being false). so, what's the certainty of the conclusion 'therefore, support for x has grown between days 1 and 2'? I suppose that if there's a 5% chance of each precept being wrong, and two precepts (i.e., 2 chances for a precept to be wrong), then there'd be a 10% chance of... what? the conclusion being not neccesarily true? The certainty of the conclusion seems as if it'd be 10%, but that feels a tad wrong. e.g., precept 2 could be wrong, but in actual fact on day 2 support could have been 60%, thus the conclusion would still be correct. so, yeah, basically how do the certainty intervals combine in this case to give a certainty for the conclusion? (for bonus points: how would that work with confidence intervals instead of certainty?)
NeonBlack Posted September 25, 2008 Posted September 25, 2008 I'm not an expert on statistics and probability, but I don't think this question is well-formed. For example, what does it mean for the statement "on day one, 45% of people are in favour of x" to be "false"?
Dak Posted September 25, 2008 Author Posted September 25, 2008 my appologies. I meant if the statement was false, then z% of people would be in favour of x on day 1, where z is not 45. i've mostly seen statements of certainty (as opposed to confidence intervals) on public oppinion polls, hence why i worded my example like that. (think estimates of parent-population mean based on sample mean: you usually end up being able to say 'there is x % chance that the parent population mean is between y and z' iirc)
Josy Posted September 29, 2008 Posted September 29, 2008 Since the proportion of the population that supports x is a continuous quantity, it's not simply a question of true or false; presumably you'd model the proportion of the parent population as a normal distribution with a mean of 45% (or 50% on Day 2) and a s.d. of something or other, then move forward from there. It's a while since I did any stats as well, so I can't really be much use on this.
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