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sam30317 Group Title

What method can researchers employ in order to counter bias in their sampling? a. snowball sampling b. weighting c. convenience sample d. non-random surveying

  • 2 years ago
  • 2 years ago

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  1. geoffb Group Title
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    Some of those are examples of bias, so they wouldn't be right. See if you can eliminate some options; we're here to help, not give the answer.

    • one year ago
  2. sam30317 Group Title
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    I had to ask because A and C were considered the same in my book. So I am unable to eliminate any answers

    • one year ago
  3. geoffb Group Title
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    Convenience sampling is taking who is available. Snowball sampling is having current participants recruit future participants. Both are biased on their own, so they would hardly serve to *counter* sampling bias.

    • one year ago
  4. sam30317 Group Title
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    Lol, my book didnt even distinguish the difference between the two. thanks so much. It should be D, right?

    • one year ago
  5. geoffb Group Title
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    No, it's definitely not D. A non-random sample would be biased in some way. http://en.wikipedia.org/wiki/Weight_function#Statistics

    • one year ago
  6. akc5228 Group Title
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    The answer would be weighting since counter bias isn't really about *countering* bias-ness, per see, instead it's a technique that is used to increase respondents’ willingness to answer questions honestly. So basically questions are prefaced with statements that attempt to justify an answer that may go against social group norms with an example being "recent surveys have indicated that the majority of people have difficulty saving every month".

    • one year ago
  7. sam30317 Group Title
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    oooooh, i get it now

    • one year ago
  8. geoffb Group Title
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    The usual definition of weighting, at least as I know it, is to correct for a smaller chance of being sampled. A common example is that households with numerous phone numbers have a greater chance of being surveyed, and therefore weights will account for this. I've never heard of influencing respondents to answer honestly as weighting. If anything, it sounds like a bias (or at least an opportunity to impart bias) in itself.

    • one year ago
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