Chapter 7 Inquizitive

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over-sampling

unbiased

Researchers conducting an online survey collect 50 men and 50 women in order to have equal gender representation.

quota sampling

A researcher approaches every fifth shopper who walks into a grocery store.

systematic sampling

These are the results of a BuzzFeed poll about superstitions with 29,000 participants. To whom can we likely generalize the results of this poll?

the 29,000 participants of the BuzzFeed poll

A college administrator knows that 30% of the students at her college are from out of state, and she wants to make sure that she maintains this proportion in her survey about admission practices at the college. She has a list of all the out-of-state and in-state students and randomly selects 30 students from the out-of-state list and 70 students from the in-state list. She is using

stratified random sampling

Synonymous Sampling Terms Used in This Chapter Externally Valid

unbiased sample probability sample random sample representative sample

The student government at a college is interested in determining how important intercollegiate sports are to the students. Because all students have e-mail accounts, the student government can send a survey to all the students at the college. About 50% of the students respond. What is the most likely bias in this sample?

Self-selection

Researchers select five hospitals at random and survey all the nurses in each hospital.

cluster sampling

At the end of an online survey, participants are asked to tell their friends about it.

snowball sampling

The directors of an annual community concert want to learn the musical preferences of the audience. The directors choose 2 and 6 from a random number generator and place a survey card on every sixth seat beginning with the second seat. All the cards are returned as the audience leaves. They are using

systematic sampling

Synonymous Sampling Terms Used in This Chapter Unknown External Valid

biased sample nonprobability sample nonrandom sample unrepresentative sample

sampling techniques that use meaningful categories from the population (e.g., demographics) and involve recruiting a certain number of participants from each of the categories in the population.

oversampling stratified random sampling quota sampling

A researcher at a nearby university wants to look at what teachers in a certain school district think about new policy changes. The researcher makes a list of all the schools in the district and uses a random number generator to select five schools from the district. Then the researcher interviews every teacher at each of those five schools. The researcher is using

Cluster sampling

snowball sampling

biased

A survey interested in comparing prisoners to non-prisoners includes prisoners as 10% of its sample, even though they only make up 2.5% of the total population.

oversampling

Karim is investigating the well-being of health care workers in his county during the COVID-19 pandemic. He notes that the health care workers in his county consist of 15% physicians, 50% nurses, and 35% administrative staff. He is considering several different sampling techniques for his study Karim is concerned that 15 physicians might not give him a precise statistical estimate, so he could recruit more physicians and then adjust the results later.

oversampling

Dr. Saetang is conducting a study on the experience of being a racial minority on a college campus. He goes to the Asian Student Association, Black Student Union, and Hispanic Student Group on his campus to recruit Asian, Black, and Hispanic participants for his study. Dr. Saetang is using

purposive sampling

Researchers choose students at random by selecting the last digit of their student IDs.

simple random sampling

Jada is working on a study focused on attention span in children and notices that 11-year-old boys are underrepresented in her sample. After her 11-year-old brother participates in her study, she asks him to distribute flyers about the study to his male classmates and soccer team. Jada is using

snowball sampling

Karim is investigating the well-being of health care workers in his county during the COVID-19 pandemic. He notes that the health care workers in his county consist of 15% physicians, 50% nurses, and 35% administrative staff. He is considering several different sampling techniques for his study Karim could randomly select 15 physicians, 50 nurses, and 35 administrative staff for his sample of 100 participants.

stratified random sampling

systematic sampling

unbiased

Researchers select children at three different elementary schools at random by birth date

multistage sampling

purposive sampling

biased

probability sampling

unbiased

stratified random sampling

unbiased

convenience sampling

biased

The campus safety committee has asked Professor Ibrahim to study bicycling on his campus. He trains two observers to rate the safety behaviors of cyclists at various locations around campus. He randomly selects 10 observation locations from the places where bicycles can be ridden on campus and randomly selects five 1-hour durations for each location. He has his observers make observations at each of the 10 places for each of the five durations. Dr. Ibrahim is using

multistage sampling

Dr. Khan asks his intro psych students to fill out a survey on sleep quality and stress after class.

convenience sampling

What kind of sample is best for external validity?

a sample where each member of the population has an equal chance of being selected

Karim is investigating the well-being of health care workers in his county during the COVID-19 pandemic. He notes that the health care workers in his county consist of 15% physicians, 50% nurses, and 35% administrative staff. He is considering several different sampling techniques for his study Karim could randomly select five hospitals from his county and recruit all of the health care workers from those five hospitals.

cluster sampling

Karim is investigating the well-being of health care workers in his county during the COVID-19 pandemic. He notes that the health care workers in his county consist of 15% physicians, 50% nurses, and 35% administrative staff. He is considering several different sampling techniques for his study Karim could randomly select five hospitals from his county and then randomly select 50 health care workers from each of the selected hospitals.

multistage sampling

Karim is investigating the well-being of health care workers in his county during the COVID-19 pandemic. He notes that the health care workers in his county consist of 15% physicians, 50% nurses, and 35% administrative staff. He is considering several different sampling techniques for his study Karim could visit a local hospital and pass out his survey to health care workers that walk by until he reaches his goal of 15 physicians, 50 nurses, and 35 administrative staff.

quota sampling


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