Respuesta :
Answer: 1. Survivorship bias
2a. Self-selection bias
2b. Undercoverage bias
3. Voluntary response bias
4. Response bias
Step-by-step explanation:
Sampling bias occurs when a representative of a population was chosen in such a way that aspects of the population had a lower probability of being sampled. For the given scenarios;
1. A political poll is conducted by contacting people on landline phones. The pollsters did not keep track of how many people they contacted who did not respond. : This is Survivorship bias. It occurs when the polled results which are recorded at the end, are not a random set of those present at the start of the polls. Polls who fell out of view are ignored.
2. A political poll is administered by contacting people on landline phones. The pollsters contacted 20,000 households and 4747 agreed to speak with the callers. : It is both Self - selection bias and Undercoverage bias. Self - selection bias occurs when a small sample that is not representative of the entire population voluntarily participates in a survey. Their opinion might not represent those of the entire population. It is also Undercoverage bias because just a few segments of the entire population were surveyed.
3. A political poll is conducted by setting up a booth at a local shopping mall and inviting passersby to share their opinions. : It is a Voluntary Response bias because the volunteers are self - selected. The passersby could decide or decide not to participate.
4. A political poll asks the question, ' If you found out that candidate A was given a large sum of money by special interest group B, would that change your opinion of how hypocritical candidate A is?': It is
a Response bias because the question is worded in such a way as to solicit some sort of biased response.
The type of sampling bias which are used in the following scenarios include:
- Survivorship bias
- a. Self selection bias
- Undercoverage bias
- Voluntary response bias
- Response bias
Sampling Bias
This refers to the selection of a member of a population based on certain conditions or characteristics in a way that they have a higher chance of being selected.
For example, survivorship bias has to do with the logical error which occurs when a member of a population is selected and some other members are ignored, because of visibility issues.
Read more about sampling bias here:
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