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This is the questions I know how to do it but I dont know how I would figure out the mean for this, which is needed to find the confidence level.
Total Sample 1116 Golfers from sample 177 16% Non Golfers from sample 939 84% Total Population 75,700,000 36,900,000 28,300,000 27,800,000 21,900,000 17,100,000 207,700,000 32,941,666.67 Quote:
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#2 |
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Assuming that each respondent's answer, coded as 0/1 is a Bernoulli trial, then (Sum Xi)/ n, i.e. the proportion, will behave like the mean.
Now, the estimation should be based in the sampling procedure used, so I assume the income information will be used as sampling weights or as strata information.
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#3 | |
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and what if the second question is like 2. Estimate with 95% confidence the number of golfers who earn at least $75,000. Please help me, I am waiting online... Thanks a lot.. |
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#4 |
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Do you know what a sampling weight is? Or a probability weight? It's just a number that how many persons in the population are represented by each observation in your sample.
If you are using a statistical software you should just estimate a total and specify the weights. Perhaps this is new to you, so maybe in your assignment the economic information is for certain post-stratification procedure. It would depend on the topic you are studying in class
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#5 | |
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Could you check my job for me please? I post it on http://talkstats.com/showthread.php?p=26753#post26753 I really appreciate for it... |
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#6 |
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The confidence interval around a sampled proportion (p_hat) is given by the formula:
p_hat +/- z_alpha/2 * sqrt[ {p_hat * (1 - p_hat)} / n ] in your example the 95% CI for golfers would be: 0.16 +/- 1.96 * sqrt [ (0.16)(0.84) / 1116 ] 0.16 +/- 0.022 |
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