Chapter 6

Question 1

sample

Answer 1

subset of population selected for study

Question 2

sampling

Answer 2

process of deciding what/ who to include in sample

Question 3

target population

Answer 3

social scientists want to make generalizations about (specific, abstract, non-human aka corporations)

Question 4

population parameters

Answer 4

represents true value of population (hard bc of time, resources, frequency and limits # of questions)

Question 5

census

Answer 5

study that includes data on every member of a population

Question 6

sampling strategy means that the observed value is….

Answer 6

true value + systematic error + random error

Question 7

types of errors

Answer 7

systematic (can’t be estimated, only discuss direction of bias)
random (unbiased, can be estimated using stats)

Question 8

probability sample needs _____ to remove ______ and estimate _____.

Answer 8

random selection
systematic errors
random errors

Question 9

probability sampling steps

Answer 9

identify
- target population
- sample size
- sampling frame
select sampling process
- simple random or
systematic
- cluster
- stratified

Question 10

sampling frame

Answer 10

list of members to draw from for sample

Question 11

simple random sampling & problem

Answer 11

everyone has same probability of being selected (same with each pair)
use random # generator
problem: may be nonrepresentative

Question 12

systematic sampling & problem

Answer 12

everyone has same probability
randomly select first one, then every nth gets picked
problem: order may create bias, consecutive cases won’t be selected

Question 13

cluster sampling & advantage

Answer 13

no available sampling frame
divide target population into clusters
select clusters randomly
get sampling frame for selected clusters then select people randomly from each cluster
advantage: improves feasibility and lowers $$$

Question 14

stratified sampling & advantage

Answer 14

obtain sampling frame then divide population into strata, select people randomly from all strata, # of people reflects population from each strata
advantage: prevent samples from being non-representative due to chance and oversample small groups

Question 15

weighting

Answer 15

how much each person in sample counts
oversampled = less weight

Question 16

formula to calculate weight

Answer 16

population size OVER sample size

Question 17

post survey weighting (response rate & nonresponse) calculation

Answer 17

Response rate = # responses OVER # of invitations x 100%
nonresponse = 100 - Response rate (can create systematic error)

Question 18

what can nonresponse rate create?

Answer 18

systematic errors

Question 19

why use probability sampling?

Answer 19

unbiased and the difference between sample estimate and population parameters is due to random chance
(no systematic errors and estimate random sampling errors)

Question 20

margin of error

Answer 20

amount of uncertainty in estimate. equals distance between estimate and boundary of confidence interval
square root of sample size

Question 21

how to calculate confidence interval and the mean

Answer 21

CI: lower bound = mean - MOE
upper bound = mean + MOE

Mean = lower + upper divided by 2

Question 22

A poll estimates the 95% confidence interval of support for a
senatorial candidate to be between 39% and 43%

Answer 22

1. find centre of confidence interval
2. upper bound - middle = MOE

Question 23

larger sample size means ____

Answer 23

smaller MOE

Question 24

what type of error is margin of error?

Answer 24

random error

Question 25

nonprobability samples are _____ and are subject to _______ & ______.

Answer 25

not randomly selected people systematic errors low generalizability

Question 26

nonprobability samples can ____

Answer 26

gather more & better info on nonrepresentative samples

Question 27

types of non-probability sampling

Answer 27

1. convenience 2. purposive 3. sequential 4. snowball

Question 28

convenience nonprobability sampling

Answer 28

select anyone, cheap & easy, systematic errors

Question 29

purposive nonprobability sampling

Answer 29

selecting cases based on 1. access & quality 2. typicality 3. extremity 4. importance 5. deviance 6. contrasting outcomes 7. key differences 8. past experiences

Question 30

sequential nonprobability sampling

Answer 30

collect more data based on already collected data key informants sampling for range saturation

Question 31

snowball nonprobability sampling

Answer 31

start with 1 person then ask them to gather people hidden populations

Question 32

ways to minimize systematic errors

Answer 32

random selection probability sampling

Question 33

ways to minimize random error

Answer 33

larger sample size can use weight, oversampling or post-survey weighting to adjust random error

Question 34

Dr. Olson passes out a survey to his introductory sociology course. He would like to generalize the results of this survey to all college students. Which type of error should Dr. Olson be concerned with?

Answer 34

Systematic error Systematic error occurs when there are systematic differences between our sample and the target population.

Question 35

What is an important potential benefit to nonrepresentative samples?

Answer 35

The similarity of people in a nonrepresentative sample can make it easier to identify a cause-and-effect relationship

Question 36

A recent Pew poll suggests that Pew is 95% confident that between 65% and 73% of millennials feel negatively about the direction of the U.S. The sample size for this survey was 3,000 millennials. What is the margin of error?

Answer 36

4%

Question 37

A recent Pew poll suggests that Pew is 95% confident that between 65% and 73% of millennials feel negatively about the direction of the U.S. The sample size for this survey was 3,000 millennials. What sample size would Pew need to decrease the margin of error to 1.5%?

Answer 37

12,000

Question 38

In political exit polling, where no sampling frame can be made in advance, which type of sampling makes the most sense?

Answer 38

Systematic sample

Question 39

Match each type of sample with the example that best fits. 1) Cluster sample 2) Stratified sample 3) Systematic sample A) A sociologist first divides registered drivers from a list of motor vehicle registrations into five-year age groups (e.g., 18-22, 23-27, 28-32, etc.), then randomly selects four age groups, and finally randomly selects individuals only from those four age groups B) A sociologist first divides registered drivers from a list of motor vehicle registrations into 5-year age groups (e.g., 18-22, 23-27, 28-32, etc.) and randomly selects 10% of the individuals from each age group C) A sociologist picks every 10th person from a list of motor vehicle registrations to create a sample of registered drivers

Answer 39

1) A 2) B 3) C

Question 40

To make sure that smaller groups are represented properly in a study, a researcher might implement which type of sampling strategy to avoid pure chance from causing their sample to be nonrepresentative?

Answer 40

Stratified sample

Question 41

To keep expenses down from having to travel to every state to conduct a survey, a researcher could instead implement which type of sampling strategy in which they would only survey randomly selected individuals in randomly selected states?

Answer 41

Cluster sample

Question 42

How many conditions must be met to establish causality?

Answer 42

3

Question 43

what strategy allows researchers to make a decision on what additional data they need based on current findings?

Answer 43

Sequential sampling

Question 44

what purposive sampling strategy allows researchers to expand respondents range of experiences?

Answer 44

sampling for range

Question 45

since we can't rule out systematic errors from nonprobability samples, _____ only applies to probability samples

Answer 45

margin of error