Research Sampling

Question 1

research population

Answer 1

a group sharing some common characteristic, (cannot realistically study)

Question 2

Sample

Answer 2

set of individuals that represent the population (subset)

Question 3

representative sample

Answer 3

sample with the same characteristics as the population

Question 4

biased sample

Answer 4

sample with different characteristics from those in the population

Question 5

selection bias

Answer 5

survey return rate, researchers going door to door

Question 6

power analysis

Question 7

resource equation

Answer 7

E= (total nb of animals)-(total number of groups)
E is the degree of freedom of ANOVA

Question 8

Non-probability sampling

Answer 8

population is not completely known-> difficult to identify size, 2 methods:convenience and quota

Question 9

convenience sampling

Answer 9

sampling method where participants are easy to access and available to participate

Question 10

convenience sampling examples

Answer 10

setting up booths, volunteers

Question 11

quota sampling

Answer 11

identify a subgroup, then choose from each subgroup to get a quota

Question 12

simple quota sampling

Answer 12

little is known about the characteristics of a population:
brain activity of 20 students taking NEUR course after drinking coffee : 10 in the AM, 10 in the PM

Question 13

proportionate quota sampling

Answer 13

demographics known and proportionately represented in sample :
brain activity of 20 students taking NEUR course after drinking coffee : CUneuro program: 60% F,40%M - 12M, 8F

Question 14

probability sampling

Answer 14

must know the exact size of population, based on random sampling

Question 15

simple random sampling

Answer 15

all individuals have equal chance of being selected, each one independent of the other

Question 16

simple random sampling with replacement

Answer 16

after each selection, ind. is added back to the pool, can be chosen more than once

Question 17

simple random sampling without replacement

Answer 17

after selection, ind. is removed from the pool, probability changes w/ each selection

Question 18

systematic sampling

Answer 18

sampling method where you choos every n^th (ex: every 4th participant) , more representative sample

Question 19

stratified random sampling

Answer 19

population is divided into strata (subgroup) then participants selected from each strata.

Question 20

proportionate stratified sampling

Answer 20

select different proportion (%) from each strata, depends on what representation in actual pop. , difficult to compare between strata if some are smaller % of pop.

Question 21

Cluster sampling

Answer 21

sampling method where pop. can be identified into clusters then choose from a proportion of the clusters