text: # An Overview of Simple Random Sampling (SRS)
  
  Image Source: Statistical Aid: A School of Statistics
  
  ### Simple random sampling
  
  Simple random sampling is considered the easiest and most popular method of probability sampling. To perform simple random sampling, all a researcher must do is ensure that all members of the population are included in a master list, and that subjects are then selected randomly from this master list.
  
  While simple random sampling creates samples that are highly representative of the population, it can be time consuming and tedious when creating large samples.
  
  The following 8-step procedure may be followed in drawing a simple random sample of n units from a population of N units.
  
  •     Assign serial numbers to the units in the population from 1 through N.
  •      Decide on the random number table to be used.
  •      Choose an N-digit random number from any point in the random number table.
  •      If this random number is less than or equal to N, this is your first selected unit.
  •      Move on to the next random number not exceeding N, vertically, horizontally or in any other direction systematically and choose your second unit.
  •      If at any stage of your selection, the random number chosen exceeds N, discard it and choose the next random number.
  •      If, further, any random number is repeated, it must also be discarded and be replaced by a fresh random number appearing next.
  •      The process stops once you arrive at your desired sample size.
  
  There are two approaches that aim to minimize any biases in the process of simple random sampling:
  
  Application of simple random sampling
  
  •      A list of all members of population is prepared. Each element is marked with a specific number (suppose from 1 to N).
  •      items are chosen among a population size of N. This can be done either with the use of random number tables or random number generator software.
  •      The Aromatic Company is planning to conduct a study to estimate the proportion of toilet soap users who prefer a certain color or flavor of their product. A simple random sample of customers may be used for this purpose. It is assumed in this case that a list (sampling frame) of the consumers is available to the research team.
  •      A forester in Chittagong Hill Tracts may wish to estimate the volume of timber or proportion of diseased trees in a forest by se geographic points in the area covered by the forest and then attaching a plot of fixed size and shape to that point. All the trees within the sample plots may be studied. But again the basic design is a simple random sample.
explanation: The document provides an overview of simple random sampling (SRS), explaining its definition, procedure, and applications. It does not contain any specific math question or answer.
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distilabel_metadata.content: # An Overview of Simple Random Sampling (SRS)
  
  Image Source: Statistical Aid: A School of Statistics
  
  ### Simple random sampling
  
  Simple random sampling is considered the easiest and most popular method of probability sampling. To perform simple random sampling, all a researcher must do is ensure that all members of the population are included in a master list, and that subjects are then selected randomly from this master list.
  
  While simple random sampling creates samples that are highly representative of the population, it can be time consuming and tedious when creating large samples.
  
  The following 8-step procedure may be followed in drawing a simple random sample of n units from a population of N units.
  
  •     Assign serial numbers to the units in the population from 1 through N.
  •      Decide on the random number table to be used.
  •      Choose an N-digit random number from any point in the random number table.
  •      If this random number is less than or equal to N, this is your first selected unit.
  •      Move on to the next random number not exceeding N, vertically, horizontally or in any other direction systematically and choose your second unit.
  •      If at any stage of your selection, the random number chosen exceeds N, discard it and choose the next random number.
  •      If, further, any random number is repeated, it must also be discarded and be replaced by a fresh random number appearing next.
  •      The process stops once you arrive at your desired sample size.
  
  There are two approaches that aim to minimize any biases in the process of simple random sampling:
  
  Application of simple random sampling
  
  •      A list of all members of population is prepared. Each element is marked with a specific number (suppose from 1 to N).
  •      items are chosen among a population size of N. This can be done either with the use of random number tables or random number generator software.
  •      The Aromatic Company is planning to conduct a study to estimate the proportion of toilet soap users who prefer a certain color or flavor of their product. A simple random sample of customers may be used for this purpose. It is assumed in this case that a list (sampling frame) of the consumers is available to the research team.
  •      A forester in Chittagong Hill Tracts may wish to estimate the volume of timber or proportion of diseased trees in a forest by se geographic points in the area covered by the forest and then attaching a plot of fixed size and shape to that point. All the trees within the sample plots may be studied. But again the basic design is a simple random sample.
distilabel_metadata.role: user
distilabel_metadata.raw_output_q_a_detector_0: The document provides an overview of simple random sampling (SRS), explaining its definition, procedure, and applications. It does not contain any specific math question or answer.
  
  Label: no-question