Chapter 7

Question 1

Population

Answer 1

all individuals that the research applies to

ex- study on whether CU students are happier when puppies are around, the population is all CU students

Question 2

census

Answer 2

when you measure the entire population

Question 3

sample

Answer 3

group of people you got from the population to be in your study

Question 4

sampling frame

Answer 4

list of everyone in the POPULATION

this is how you get your sample

Question 5

population vs sample

Answer 5

population is the entire group & the sample is only the part of that population you are actually measuring

Question 6

Representative samples

Answer 6

• represent the population
• random sample of everyone in the population
• everyone has an equal chance of being in your sample

Question 7

simple random

Answer 7

have the SAMPLING FRAME & then randomly choose how may people you want in your study
-everyone has an equal chance
-this is not randomly talking to people as they walk around campus
ex- CU students are the population, get all of the ID numbers of EVERY student & randomly pick 50 students

Question 8

systematic sampling

Answer 8

get a SAMPLING FRAME & pick a random number and then you take the sample & divide it by the desired amount for the survey & pick every #th one
ex- the researcher started by selecting two random numbers - 4 & 7. the researcher then started on the 4th person and picks every 7 th name

Question 9

Cluster Sampling

Answer 9

randomly choose a group and then you choose a cluster & take EVERYONE in that cluster
ex- want to study undergraduates in Colorado, choose CU, DU, Mines, & CSU as your cluster & look at ALL of those students

Question 10

multistage sampling

Answer 10

you start out by taking a population & then take out clusters and then choose another form of sampling to get your results
ex- 7 decks pf cards & then randomly choose 3 of those decks, then use a simple random sample on those 3 decks

Question 11

stratified random smaple

Answer 11

researchers selects particular demographic categories on purpose and then randomly selects individuals within each of the categories
ex- a group of researchers might want to be sure their sample of 1,000 Canadians includes people of South Asian descent in the same population as in canadian population. So they have two two categories (strata) in their population: South Asian Canadians and other Canadians. In a sample if 1,000 they include at least 40 members of South ASIan. It is imported that both categories are selected randomly

Question 12

oversampling

Answer 12

we have a specific demographic we want to sample, we know there isn’t a lot so we need to oversample (over represent)
ex- in a sample of 1,000 the researchers want to make sure South Asians are represented & the researchers population is only 4% so instead of sampling only 40 they sample 100

Question 13

what are all the representative samples?

Answer 13

simple random 
systematic sampling 
cluster sampling 
multistage sampling 
stratified random sampling 
oversmapling

Question 14

Bias sampling

Answer 14

external validity isn’t vital to the study goals, researcher might be okay with a bias sample

Question 15

convince sampling

Answer 15

sample whatever is convent to you

ex- most studies being sophomore psych students- taking a survey of people in your class

Question 16

purposive sampling

Answer 16

go in looking for specific characteristics or demographic (someone advertising)
ex- specifically advertising for it, having flyers looking for people that are left handed

Question 17

snowball sampling

Answer 17

find one person in that demographic & asl them to ask other people they know in the same demographic to be in there study
ex- find someone who has a child between the age of 3-5 & then have them ask there other friends

Question 18

quota sampling

Answer 18

researcher identifies subsets of the population of interstate’s & then sets a target number for each category in the sample (80 Asian Americans, 80 African Americans, & 80 Latinos). Then the researcher samples from the population of interests randomly until the quota is filled

Question 19

difference between quota sampling & stratified random sampling

Answer 19

they both look at subsets of a population but in quota sampling = the participants are elected non randomly (convince sampling or purposive sampling) while stratified random sampling = they are seated using a random selection technique

Question 20

all of the bias samples

Answer 20

convince sampling
purposive sampling
snowball sampling
quota sampling

Question 21

do you need a representative sample to make it a good sample?

Answer 21

it depends one of you are running an experiment & randomly assigning them to different things, then it doesn’t really matter