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Bias in Surveys

Recognize and Reduce it

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HW

Turn in your 3.3.2 HW

Today’s HW due next class and on AP Classroom

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100% of AP Statistics students agree, a hot dog is a taco.

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100% of AP Statistics students agree, a hot dog is a taco.

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100% of AP Statistics students agree, a hot dog is a taco.

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If you had to do it over again, would you have children?

Ann Landers, the advice columnist, asked parents this question.

10,000 people wrote in.

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If you had to do it over again, would you have children?

A more carefully designed survey later showed this.

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Big Idea

  1. Explain how undercoverage, nonresponse, question wording, and other aspects of a sample survey can lead to bias.
  2. Bias arises when procedures skew data being collected, leading to overestimation or underestimation of the population.
  3. Watch out for bias in surveys—it's pervasive.

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The two main types of bias are

Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

With Your Partner

Prepare an explanation of what your thing is showing.

Explain the type of bias it illustrates.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Where There Is a Will

A quick blurb from the podcast to illustrate Response Bias

Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

David Kestenbaum

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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How does Gallup polling work?

Gallup polls aim to represent the opinions of a sample of people representing the same opinions that would be obtained if it were possible to interview everyone in a given country.

The majority of Gallup surveys in the U.S. are based on interviews conducted by landline and cellular telephones. Generally, Gallup refers to the target audience as "national adults," representing all adults, aged 18 and older, living in United States.

The findings from Gallup's U.S. surveys are based on the organization's standard national telephone samples, consisting of directory-assisted random-digit-dial (RDD) telephone samples using a proportionate, stratified sampling design. A computer randomly generates the phone numbers Gallup calls from all working phone exchanges (the first three numbers of your local phone number) and not-listed phone numbers; thus, Gallup is as likely to call unlisted phone numbers as listed phone numbers.

Within each contacted household reached via landline, an interview is sought with an adult 18 years of age or older living in the household who has had the most recent birthday. (This is a method pollsters commonly use to make a random selection within households without having to ask the respondent to provide a complete roster of adults living in the household.) Gallup does not use the same respondent selection procedure when making calls to cell phones because they are typically associated with one individual rather than shared among several members of a household.

When respondents to be interviewed are selected at random, every adult has an equal probability of falling into the sample. The typical sample size for a Gallup poll, either a traditional stand-alone poll or one night's interviewing from Gallup's Daily tracking, is 1,000 national adults with a margin of error of ±4 percentage points. Gallup's Daily tracking process now allows Gallup analysts to aggregate larger groups of interviews for more detailed subgroup analysis. But the accuracy of the estimates derived only marginally improves with larger sample sizes.

After Gallup collects and processes survey data, each respondent is assigned a weight so that the demographic characteristics of the total weighted sample of respondents match the latest estimates of the demographic characteristics of the adult population available from the U.S. Census Bureau. Gallup weights data to census estimates for gender, race, age, educational attainment, and region.

Read more about conducting polls in Gallup's longer paper, "How Are Polls Conducted?"

Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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Selection Bias

The sample used for analysis is not representative of the entire population.

This leads to skewed or inaccurate conclusions due to the non-random selection of participants.

Response Bias

Individuals provide distorted or inaccurate answers.

This can stem from factors like conformity to norms, compliance, extreme responses, or non-participation.

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To reduce...

Selection Bias

Response Bias

  • Randomize how your samples are picked.
  • Make sure everything in the population has an equal chance of getting picked.
  • Ensure that everyone in the sample responds.
  • Carefully word and field-test survey questions.
  • Make sure you collect data in a neutral way.

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Ideas to Think About

Are the following statements true or false?

Random sampling is a good way to increase response rates.

Use a convenience sample when your population contains unusual or rare members to make sure they are represented.

Increasing the sample size tends to reduce bias in a survey.

Google surveys get reliable response rates.

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Practice

There are three scenarios on your worksheets.

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Big Idea

  • Explain how undercoverage, nonresponse, question wording, and other aspects of a sample survey can lead to bias.
  • Bias arises when procedures skew data being collected, leading to overestimation or underestimation of the population.
  • Watch out for bias in surveys—it's pervasive.

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