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Author Question: Discuss the various implications of the central limit theorem to the practice of ... (Read 74 times)

tfester

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on: Jun 29, 2018
Discuss the various implications of the central limit theorem to the practice of sampling.

Question 2

A researcher is examining the row and column totals in a contingency table of stores shopped at by gender. What are these called?
 a. marginals
  b. subtotals
  c. totals
  d. running totals


gasdhashg

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Reply #1 on: Jun 29, 2018
Answer to Question 1

The central limit theorem can be applied only when certain conditions hold during probability sampling (it doesn't hold for non-probability sampling methods). Among its implications for sampling are:
 If the population distribution is normal, the sampling distribution of the mean will be normal for all sample sizes.
 If the population distribution is not normal, the sampling distribution of the mean approaches normality as the sample size increases.
 The mean of the sampling distribution (of the mean) is an unbiased estimate of the population mean.
 The standard error of the sampling distribution (of the mean) is the population standard deviation divided by the square root of the sample size.

Answer to Question 2

A


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