Participant Sampling

Question 1

population

Answer 1

all people (or items locations etc) of interest
who you want your results to generalize to

Question 2

sample

Answer 2

individuals in your study

Question 3

probability sampling

Answer 3

use some form of random selection
requires setting up a procedures that assures the different members of your population have equal probabilities of being chosen

Question 4

non-probability

Answer 4

not random, may or may not represent population well even with a large sample size.

convenience sampling
purposvie sampling

Question 5

Simple random sampling

Answer 5

each has an equal changes of being selected. (picking from hat)

Question 6

systematic random sampling

Answer 6

selecting one member randomly and then choose addition members at evenly spaced intervals. select every 5th on the list

Question 7

stratified samlping

Answer 7

population divided into different groups based on criteria

simple random from each group

Question 8

cluster sampling

Answer 8

select clusters from population on the basis of simple random sampling, then same all the people in the cluster

Question 9

multistage sampling

Answer 9

combine different methods of probability sampling

cluster, then random

Question 10

convenience sampling

Answer 10

participants chosen not random - like college students, local volunteers

Question 11

purposive sampling

Answer 11

specific predefined groups that we seek

sampling for proportionality is not the primary concerns

Question 12

quota sampling

Answer 12

select non randomly according to fixed quota

can be proportional or non-proportional

Question 13

heterogeneity sampling

Answer 13

sample to include all opinions/views, but not representing these views proportionately

Question 14

snowball sampling

Answer 14

eligible participants to recommend others who may qualify

Question 15

random assignment

Answer 15

ideal way to divide your sample into groups

Question 16

counterbalancing

Answer 16

used to overcome order effects

Question 17

within-subjects counterbalancing

Answer 17

each subject goes through each condition one or more times

reverse or block

Question 18

across-subjects counterbalancing

Answer 18

each gets one sequence but they differ across people

Question 19

partial counterbalance

Answer 19

randomized counterbalancing,
-each different random sequence
Latin square counterbalancing

Question 20

Balanced latin square counterbalancing

Answer 20

A square of sequences such that each condition appears

only once in any order position in the sequences AND follows each other condition an equal number of times