OpenIntroStat/openintro-statistics

Ch 5: Understanding the variability of a point estimate and unbiasedness

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In this section we simulate samples of size n = 1000 from a population of N = 250million with the assumed proportion parameter of 0.887. And then we're say that the generated sampling distribution is centered at 0.887, and hence the estimate of p-hat = 0.887 is unbiased.

But the sampling distribution was generated assuming the true p is 0.887, so we shouldn't use the resulting sampling distribution to justify unbiasedness.

Am I missing something?

Upon further reflection, a simple solution to this confusion might be to present an example where we can assume we know true p. And then Section 5.1.4 Applying the CLT to a real-world setting would make more sense as to why what we discussed previously was not a real world setting.

I've reframed the section to use p = 0.88 instead and suppose this is the truth. This is captured in the following commit:
c800e0c