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Sampling Methods & Bias in Surveys. Convenience Sampling. Choosing individuals that are easiest to reach Example: interviewing the first 50 people that enter the grocery store. Produces sample bias: not every member of the population has the same probability of being chosen.
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Convenience Sampling • Choosing individuals that are easiest to reach • Example: interviewing the first 50 people that enter the grocery store. • Produces sample bias: not every member of the population has the same probability of being chosen
Sampling by Self Selection • Example: Conducting an interview at the mall. You, as the interviewer, choose who to interview based on your personal, professional judgment. • Produces response bias
Simple Random Sample (SRS) • Basic Idea: Label your entire population individually on strips of paper. Put the names (or numbers) in a hat and draw out a handful (the sample). • Every group of individuals have the same probability of being chosen. • Eliminates bias • Not practical for large populations
Simple Random Sample (SRS) • Definition pg 335 “A simple random sample of size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected.”
Which methods of selecting a sample of students from our class are simple random samples? • Randomly pick a table number and select the 4 students at the table. • Pick 6 names out of a hat containing the names of all class members • Choose every 4th student from an alphabetical roll sheet. • Randomly choose a month and select every student born that month.
Stratified Random Sample • Divide the population into groups of similar individuals—strata. • Choose a SRS from each of the strata. • Combine the SRS’s to get the full sample. Ex: A random sample of young people may first be separated into elementary, junior high and high school strata before being randomly selected.
Cluster Sampling • A sampling design in which entire groups or clusters are chosen at random. • Cluster sampling is usually selected as a matter of convenience, practicality, or cost. Each cluster should be heterogeneous (representative of the population), and all the clusters should be similar to each other.
Multistage Sample • Take an SRS of successively more and more detailed populations Example: US Census Household Sample • Take a sample of the 3000 counties in US • Take a sample of towns within the counties • Select a sample of blocks within the town. • Take a sample of households from within each block.
Systematic Random Sampling Example: An interviewer at the mall asks every 10th passerby to complete a survey. Systematic Sampling does not produce an SRS because every group of individuals in the population does not have the same probability of being chosen.
What is Bias? • The design of a survey is biased if it leads to systematic deviation from the population value you are trying to estimate
Response Bias—Leading Questions • Do you agree or disagree with this statement? People who commit terrible crimes of humanity that cause other people suffering and pain should be given the death sentence.
Response Bias—poorly worded questions • In your opinion is the depletion of the subaquiline layers of the Pacific causing undue stress on the geology of continental drifting tectonic plates? ?
Response Bias—privacy • Marble to his AP Statistics Class: Honestly, what do you think of me as a teacher? Response: You are the best teacher ever Reality: You talk too much and have a unibrow!!
Voluntary response bias • A sample survey is sent to 10,000 registered Democratic voters asking them to complete a survey on gun control and return the survey by mail. 89% of the respondents said they strongly favored gun control.
Nonresponse bias • Unable to contact—person is not home, does not answer the phone or does not respond by mail • Refusal to answer—person chooses not to share his/her opinion with the surveyor • Undercoverage—person can’t answer because they don’t have a phone, mailbox, internet etc. • Beware: Non-responders may have a significantly different response than rest of sample.
Moral of the story • In order to accept the sample data from a survey, much care and effort must go into the design and wording of the survey. • BIAS in the design or wording of the survey will negate all and any inferences you might make about the population as a whole.