Probability Sampling Methods: Multistage, Multiphase, and Cluster Samples


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question 1 of 3

Bradley chooses his sample by using a random number generator. Which of the following describes Bradley's method?

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1. Megan randomly chooses two homerooms in her school to whom she will give her survey. Which of the following best describes this type of sampling?

2. Bryan randomly selects 50 office buildings in his city to visit. Once entered an office building, Bryan will then randomly select 2 offices to visit. He will poll all the employees at each chosen office. Which of the following type of sampling is Bryan using?

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About This Quiz & Worksheet

There are multiple ways of gathering information from large populations. This quiz and worksheet combination will check your understanding of three different methods of probability sampling - cluster, multistage, and multiphase - and test you on the strengths and drawbacks of each type.

Quiz & Worksheet Goals

This quiz will ask students about the following:

  • How subjects are chosen for probability sampling
  • How samples are chosen in cluster and multistage sampling
  • What data is gathered from in multiphase sampling
  • What type of sampling is being used in a given example

Skills Practiced

This quiz and worksheet provide students with practice in these skills:

  • Reading comprehension - ensure that you draw the most important information from the related lesson on sampling methods
  • Distinguishing differences - compare and contrast topics from the lesson, such as multistage and multiphase sampling
  • Knowledge application - use your knowledge to answer questions about each sampling method

Additional Learning

View the lesson Probability Sampling Methods: Multistage, Multiphase, and Cluster Samples for more insight into sampling. The lesson contains the following objectives:

  • Describe why multistage sampling allows for a broader range than cluster sampling
  • Explore ways in which multiphase sampling provides the most comprehensive results
  • Explain how bias can result from cluster sampling