Consider Example A of Section 7.2 in your Rice textbook. The population consists of N = 393 short-stay hospitals. Let 2; denote the number of patients discharged from the ith hospital during January 1968. The proportion of hospitals with fewer than 1000 discharges is p = 0.654. Suppose that the total number of hospitals with fewer than 1000 discharges is estimated from a simple random sample without replacement of size n = 25. Use the Central Limit Theorem and R to sketch the approximate sampling distribution of the estimate.

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Consider Example A of Section 7.2 in your Rice textbook. The population consists of N = 393
short-stay hospitals. Let x; denote the number of patients discharged from the ith hospital during
January 1968. The proportion of hospitals with fewer than 1000 discharges is p = 0.654. Suppose
that the total number of hospitals with fewer than 1000 discharges is estimated from a simple
random sample without replacement of size n = 25. Use the Central Limit Theorem and R to
sketch the approximate sampling distribution of the estimate.
Hint: You will need the definition of the population total from Section 7.2.
Transcribed Image Text:Consider Example A of Section 7.2 in your Rice textbook. The population consists of N = 393 short-stay hospitals. Let x; denote the number of patients discharged from the ith hospital during January 1968. The proportion of hospitals with fewer than 1000 discharges is p = 0.654. Suppose that the total number of hospitals with fewer than 1000 discharges is estimated from a simple random sample without replacement of size n = 25. Use the Central Limit Theorem and R to sketch the approximate sampling distribution of the estimate. Hint: You will need the definition of the population total from Section 7.2.
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