EC285 Chapter Notes - Chapter 10: Central Limit Theorem, Standard Deviation, Categorical Variable

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8 Jan 2017
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Ec(cid:1006)85: ch. (cid:1005)(cid:1004) sa(cid:373)pli(cid:374)g distributio(cid:374)s p is the true proportion (probability) and (cid:1868) is the recorded sample proportion of successes. The distribution of proportions over all possible independent samples from the sample population is called the sampling distribution of the proportions. E. g. the true proportion of credit cardholders who increased spending by more than is 0. 21, for sample size 1000. = (cid:1868)(cid:1869)(cid:1866) (cid:1830)(cid:4666)(cid:1868) (cid:4667)= (cid:1868)(cid:4666)(cid:883) (cid:1868)(cid:4667) (cid:1866) (cid:4666)(cid:1868) (cid:4667)=(cid:1868) (cid:1830)(cid:4666)(cid:1868) (cid:4667)= (cid:882). (cid:884)(cid:883) (cid:882). 79 (cid:883)(cid:882)(cid:882)(cid:882) =(cid:882). (cid:882)(cid:883)(cid:884)9 (cid:1867)(cid:1870) (cid:883). (cid:885)% Two samples of size 1000 had proportions of 21. 1% and 20. 2% Not even one standard deviation apart and are consistent with a true proportion of 21% Difference between sample proportions is sampling error: not actually an error but a variability from one sample to another. The normal model, (cid:4666)(cid:1868), (cid:3043)(cid:3044)(cid:4667) is a sampling distribution model for the sample proportion. Independence assumption: the sampled values must be independent of each other.

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