Understanding Bias in Sampling Methods

The video tutorial explains the importance of using samples in statistical studies to estimate characteristics of a population. It highlights the potential for bias in sampling, emphasizing the need for unbiased samples to accurately represent the population. Examples of biased and unbiased samples are provided, along with a discussion on systematic sampling and how to avoid bias in surveys and experiments.

Why is it often impractical to conduct a survey on an entire population?

• All of the above.

• It is time-consuming.

• It is too expensive.

• It is not feasible for large populations.

What is a key characteristic of an unbiased sample?

• It accurately represents the entire population.

• It is smaller in size.

• It is collected from a single location.

• It includes only a specific group.

How does the size of a sample generally affect its bias?

• Sample size does not affect bias.

• Larger samples tend to be less biased.

• Smaller samples are always unbiased.

• Larger samples tend to be more biased.

In the example of the journalist surveying students, why is the sample considered biased?

• It only includes members of the Young Republicans.

• It includes a large number of students.

• It includes students from all political groups.

• It surveys students from different campuses.

What method did the shoe store use to ensure an unbiased sample?

• Surveying only boys.

• Surveying every third girl and boy.

• Surveying only girls.

• Surveying every customer.

What could potentially introduce bias in a survey conducted by a shoe store?

• Surveying every third customer.

• Surveying in the morning.

• The surveyor wearing a branded shirt.

• Surveying only on weekends.

What is a systematic sample?

• A sample collected at regular intervals.

• A sample collected from different locations.

• A sample collected randomly.

• A sample collected from a single group.

How can the phrasing of questions in a survey introduce bias?

• By being too short.

• By being too long.

• By being too complex.

• By leading respondents to a particular answer.

What is one way to reduce bias in a survey?

• Ensuring the sample is representative of the population.

• Using leading questions.

• Surveying only one demographic.

• Surveying a small group.

Why is it important to factor out bias in experiments?

• To ensure accurate and reliable results.

• To save time.

• To reduce costs.

• To make the experiment easier.