7. It is a random sampling which uses a list of all the elements in the population and then elements are being selected based

General
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  1. It is a random sampling which uses a list of all the elements in the population and then elements are being selected based from the kth consistent intervals. To get the kth interval, divide the population size by the sample size. k=N/n. A. Cluster Sampling C. Systematic Sampling B. Stratified Random Sampling D. Simple Random Sampling (SRS
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Which random sampling method uses a list of all elements in the population to select elements based on consistent intervals from the kth position?

Answer:

The description provided matches C. Systematic Sampling.

In systematic sampling, you use a list of the entire population and select every kth element from that list to form your sample. Here’s how it works step by step:

  1. List the Population: You need a comprehensive list of all the elements in your population.
  2. Determine the Sample Size (n): Decide how many elements you need in your sample.
  3. Calculate k (Interval): Determine the interval at which you’ll select elements. This is calculated by dividing the total population size (N) by the sample size (n). The formula is ( k = \frac{N}{n} ).
  4. Select the Starting Point: Randomly choose a starting point within the first k elements.
  5. Select Elements: From your starting point, select every kth element in the population list.

For example, if you have a population of 1000 elements and you want a sample size of 100, you would set k to 10 (since ( \frac{1000}{100} = 10 )). After choosing a random starting point (say, the 5th element), you would then select every 10th element afterward (5th, 15th, 25th, etc.) until you have 100 elements in your sample.

This method is advantageous because it is straightforward and easy to implement, particularly if the list is orderly and no periodicity or hidden patterns exist in the list that might bias the sample.

In contrast:

  • A. Cluster Sampling involves dividing the population into clusters, then randomly selecting whole clusters.
  • B. Stratified Random Sampling involves dividing the population into strata (or groups) and randomly selecting samples from each stratum.
  • D. Simple Random Sampling (SRS) involves randomly selecting elements from the population with each element having an equal chance of being selected.

Systematic sampling is not as random as SRS because once the starting point is chosen, the selection of other elements is fixed; however, it simplifies the sampling process and can be quite efficient in practical situations.

@anonymous11