Avoiding Bias in Statistical Research

The video tutorial discusses various types of statistical bias, including selection and response bias, and their implications on research. It provides strategies to avoid these biases, such as generating representative samples and using neutral questions. The tutorial emphasizes the importance of unbiased research for accurate conclusions.

What is statistical bias?

• A random error in data collection

• A method to ensure accurate data

• A type of data analysis technique

• The tendency of a sample statistic to misrepresent a population parameter

Which of the following is NOT a type of selection bias?

• Social desirability

• Nonresponse bias

• Undercoverage

• Convenient sample

How can undercoverage bias be avoided?

• By using a small sample size

• By making conclusions based on a single characteristic

• By ignoring certain demographics

• By ensuring the sample is representative of the entire population

What is a potential issue with convenient sampling?

• It always represents the entire population

• It can lead to biased conclusions

• It is the most accurate sampling method

• It requires complex statistical tools

What is a common strategy to address nonresponse bias?

• Sending out more surveys than needed

• Reducing the sample size

• Ignoring non-respondents

• Using only online surveys

What is a bogus pipeline?

• A method to ensure data accuracy

• A way to increase sample size

• A psychological trick to encourage truthful responses

• A type of statistical analysis

How can leading questions be avoided?

• By assuming the respondent's answer

• By asking for opinions

• By using neutral wording

• By using complex language