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Sampling Distributions MCQs – Practice Test 5 PDF Download

MCQ 21: The theorem which states that as the sample size increases the sampling distribution must approach the normal distribution is classified as:

  1. limited approximation theorem
  2. secondary limit theorem
  3. primary limit theorem
  4. central limit theorem

MCQ 22: The conditions such as large sample size to represent population and samples must be drawn randomly are included in:

  1. principle of statistical regularity
  2. principle of statistical irregularity
  3. principle of sampling error
  4. principle of inertia

MCQ 23: The measures in sampling that are results of sample analyses are called:

  1. absolute statistics parameter
  2. coverage estimators
  3. population statistics
  4. sample statistic

MCQ 24: All the values in sample distribution that can freely varies in the selected random sample from population are indicated as:

  1. degree of freedom
  2. degree of error
  3. degree of statistic
  4. degree of possibility

MCQ 25: IF the population standard deviation is not known then the formula used to calculate standard error is as:

  1. n - 1 ⁄ sample size square root
  2. s ⁄ sample size square root
  3. n + 1 ⁄ square root of s
  4. n * 2 ⁄ sample size square root

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