How to identify sources of bias in a survey - AP Statistics

Because the survey is being conducted on drivers at a gas station, people/households who do not own a motor vehicle will not be included in the survey.

Using random sampling methods alone does not reduce variability in a sample; they only reduce bias. The best way to reduce variability in an unbiased sample is to take a bigger sample—the bigger the population of the sample, the less widespread the results will be. It is important to remember that if there is bias present in a sample, a large sample population size (n value) will not be enough to overcome the bias.

Voluntary response bias usually results when those sampled are volunteers who select themselves.
Voluntary response bias can cause results to over represent those who have a strong opinion.

This is an example of undercoverage because the researcher did not speak to people who were not affiliated with a university. Therefore the researcher did not adequately sample all members of the overall population (people in the United States).

By using the words way too much and simple coffee, the researcher is introducing bias into their question by causing people to favor one response over another.

To avoid this sampling bias, the researcher should use more neutral wording, such as "Agree or diasgree- I would pay $5 or more for a coffee drink."

The correct answer (random sample of 300 students) includes a random sample which will reduce in bias and also is given to be done in person which reduces completion bias. It is also taken from the whole population of students and is a large sample which makes it a good representation of the population. Sending out a questionnaire has completion bias because the only people that will send it back will have strong and possibly biased beliefs already. The hot line has the same effect as those that have strong and biased opinions will be the ones to do it. Pulling students aside as they walk by is not a truly randomly constructed sample and using only 10 students is not a good representation of a whole college. Selecting a sample of just athletes is very biased as they will not want their programs cut.

Because the survey is being conducted on drivers at a gas station, people/households who do not own a motor vehicle will not be included in the survey.

Using random sampling methods alone does not reduce variability in a sample; they only reduce bias. The best way to reduce variability in an unbiased sample is to take a bigger sample—the bigger the population of the sample, the less widespread the results will be. It is important to remember that if there is bias present in a sample, a large sample population size (n value) will not be enough to overcome the bias.

Voluntary response bias usually results when those sampled are volunteers who select themselves.
Voluntary response bias can cause results to over represent those who have a strong opinion.

This is an example of undercoverage because the researcher did not speak to people who were not affiliated with a university. Therefore the researcher did not adequately sample all members of the overall population (people in the United States).

By using the words way too much and simple coffee, the researcher is introducing bias into their question by causing people to favor one response over another.

To avoid this sampling bias, the researcher should use more neutral wording, such as "Agree or diasgree- I would pay $5 or more for a coffee drink."

Many people are reluctant to be honest about their bad behaviors, especially if they don't believe the survey is confidential. This will cause participants to be more likely to respond with whatever is more socially acceptable.

The correct answer (random sample of 300 students) includes a random sample which will reduce in bias and also is given to be done in person which reduces completion bias. It is also taken from the whole population of students and is a large sample which makes it a good representation of the population. Sending out a questionnaire has completion bias because the only people that will send it back will have strong and possibly biased beliefs already. The hot line has the same effect as those that have strong and biased opinions will be the ones to do it. Pulling students aside as they walk by is not a truly randomly constructed sample and using only 10 students is not a good representation of a whole college. Selecting a sample of just athletes is very biased as they will not want their programs cut.

Because the survey is being conducted on drivers at a gas station, people/households who do not own a motor vehicle will not be included in the survey.

Using random sampling methods alone does not reduce variability in a sample; they only reduce bias. The best way to reduce variability in an unbiased sample is to take a bigger sample—the bigger the population of the sample, the less widespread the results will be. It is important to remember that if there is bias present in a sample, a large sample population size (n value) will not be enough to overcome the bias.

Voluntary response bias usually results when those sampled are volunteers who select themselves.
Voluntary response bias can cause results to over represent those who have a strong opinion.

This is an example of undercoverage because the researcher did not speak to people who were not affiliated with a university. Therefore the researcher did not adequately sample all members of the overall population (people in the United States).

By using the words way too much and simple coffee, the researcher is introducing bias into their question by causing people to favor one response over another.

To avoid this sampling bias, the researcher should use more neutral wording, such as "Agree or diasgree- I would pay $5 or more for a coffee drink."

Many people are reluctant to be honest about their bad behaviors, especially if they don't believe the survey is confidential. This will cause participants to be more likely to respond with whatever is more socially acceptable.