Sampling

Question 1

sampling bias

Answer 1

representative sample
biased sample

Question 2

representative sample

Answer 2

a sample that closely represents the population
#inclusitivity

Question 3

biased sample

Answer 3

some people have a better chance of being represented in the population
- not all groups are represented/some groups are overrepresented in the sample compared to general population

Question 4

probability sampling

Answer 4

• every individual has a chance of being selected
• random selection
• every individual in targeted population is identified

Question 5

nonprobability sampling

Answer 5

does not meet one of the criterias from probability sampling

Question 6

simple random sampling

Answer 6

probability sampling in which every member of the target population has an equal chance of being selected
- if there are one million people, everyone has a one in a million chance of being selected

Question 7

systematic sampling

Answer 7

• old fashion approach
  1. order all individuals in the population
  2. pick a random starting point
  3. select each nth individual

example: knocking on every fifth door in the neighborhood

Question 8

cluster sampling

Answer 8

researcher is interested in studying PSYC 70 students
let’s say there are 2,000 PSYC 70 classes UC wide
cluster sampling is randomly selecting from a few UCs but not all locations

Question 9

stratified random sampling

Answer 9

1. purposefully select particular demographic categories
2. randomly select individuals within that category
3. proportionate to their membership in the population

example:
survey = campus climate @ UCSD
1. take students by different racial ethnic groups
2. select a proportionate amount of people from each group
- group 1: 5 members = take 1 person
- group 2: 10 members = take 1 person
- group 3: 5 members = take 1 person

Question 10

cluster vs stratified sampling

Answer 10

cluster
- each cluster is heterogenous
- includes a variety of people
- some clusters are randomly sampled, others are eliminated

stratified
- each stratum is homogenous
- includes one kind of person
- all strata are proportionately sampled

Question 11

convenience sampling

Answer 11

sampling individuals who are easily accessible

Question 12

quota sampling

Answer 12

• makes sure to represent all groups
• similar to stratified sampling
• selection is NOT random
• all individuals may or may not be identified

Question 13

snowball sampling

Answer 13

asking participants to recruit other participants who are similar to them
-useful when you don’t have easy access to a particular group

Question 14

sample size and sampling error larger samples are more representative. true or false

Answer 14

false. larger samples reduce sampling error but dont reduce sampling bias (systematic error)