Skip to main content
Indietro

Introductory Statistics: Bias and Sampling Errors

I pulsanti di controllo sono stati cambiati in modalità "navigazione".
1/20

Termini in questo insieme (20)

  • What is sampling bias?

    Sampling bias occurs when the technique used to select individuals favors one part of the population over another, making the sample unrepresentative.

  • Define nonresponse bias.

    Nonresponse bias happens when individuals selected for a sample do not respond and their opinions differ from those who do respond.

  • What is response bias?

    Response bias occurs when survey answers do not reflect the true feelings of the respondents.

  • Explain voluntary response bias with an example.

    Voluntary response bias arises when respondents decide themselves whether to participate, often leading to unrepresentative samples. Example: A TV show asking viewers to call in their opinions.

  • What is undercoverage in sampling?

    Undercoverage happens when some groups in the population are left out or inadequately represented in the sample.

  • How can wording of questions cause bias?

    Biased wording can mislead respondents or influence their answers, affecting the survey's accuracy.

  • What is the difference between open and closed questions?

    Open questions allow respondents to answer freely; closed questions require choosing from predetermined options.

  • What is a sampling error?

    Sampling error is the discrepancy between a sample result and the true population result due to random selection.

  • Define nonsampling error.

    Nonsampling error results from human mistakes, biased questions, false data, or inappropriate statistical methods, including undercoverage and response biases.

  • What is nonrandom sampling error?

    Nonrandom sampling error occurs when a nonrandom method like convenience or voluntary response sampling is used, causing bias.

  • Why is sample size important?

    Sample size is the number of items or subjects in a sample; larger sizes generally provide more reliable estimates.

  • What should be considered about the source of data?

    Data should come from a reputable source to ensure accuracy and reliability.

  • How can the order of questions affect survey results?

    The order of questions can influence how respondents interpret and answer subsequent questions, potentially biasing results.

  • What is a misleading conclusion in statistics?

    A misleading conclusion occurs when sample data is reported instead of measured data or when answers are misrepresented.

  • Explain the difference between sampling error and nonsampling error.

    Sampling error is due to random chance in sample selection; nonsampling error arises from mistakes or biases unrelated to sampling randomness.

  • What is the impact of low response rates in surveys?

    Low response rates can increase nonresponse bias, reducing the representativeness of the sample.

  • Give an example of how question wording can bias responses.

    Example: Asking "Do you oppose the reduction of estate taxes?" may bias answers compared to "Do you favor or oppose the reduction of estate taxes?"

  • What is the role of sampling method in data quality?

    The sampling method determines how individuals are selected; random methods reduce bias, while nonrandom methods increase it.

  • Why can voluntary response samples be unreliable?

    Because participants self-select, leading to overrepresentation of strong opinions and bias.

  • What is the difference between bias and sampling error?

    Bias causes systematic errors making samples unrepresentative; sampling error is random variation expected in any sample.