SAMPLING

Question 1

define sampling

Answer 1

selecting participants that allow us to make generalisable inferences

Question 2

define population

Answer 2

A group of people about whom one would like to draw some meaningful conclusions

e.g.
Adolescents
People with schizophrenia
QUT Psychology undergraduates

Question 3

define sample

Answer 3

a subset of that population that is actually included in the research study

e.g.
150 Year 10 students
30 outpatients
Everyone who attends wk3 lecture

Question 4

define sampling frame

Answer 4

a list of people or elements of a population from which one might obtain a sample

e.g.
Electoral role
Telephone directory
Student enrolment list

Question 5

define census

Answer 5

a list of ALL the people comprising a particular population

Question 6

what does having a representative sample mean?

Answer 6

This simply means that you should select a sample whose typical characteristics are approximately the same as the typical characteristics of the population.

Question 7

elements/means of measuring representativeness

Answer 7

sample statistic - a numeric characteristic of the sample (measured)

population parameter - numeric characteristic of the population (often unknown)

response rate - what proportion of people responded

sampling error - the difference between sample statistic and population parameter (depends on sample size)

Question 8

what is sampling bias

Answer 8

something at impedes the representativeness of a sample

e.g. self-selection

Question 9

what are the two types of sampling procedures

Answer 9

probability

• simple random
• systematic random
• stratified
• multicluster

non-probability

• convenience
• snowball
• purposive

Question 10

define probability sampling

Answer 10

a way to ensure your sample is representative of the population based on characteristics deemed important to the study

Question 11

what is the basic principle of probability sampling

Answer 11

a sample will be representative of the population if all members have an equal chance of being selected in the sample

allows researchers to calculate the relationship between the sample statistic and population parameter

Question 12

what are the types of probability sampling

Answer 12

Simple random sample

Systematic random sample

Stratified random sampling

Multistage cluster sampling

Question 13

define a simple random sample

Answer 13

each member has an equal and independent chance of being selected

Question 14

whats the process of selection via a simple random sampling

Answer 14

> define the population
list all members
> assign numbers

• use a table of random numbers to select
• use ‘lottery’ method
• use a computer program to randomly select

Question 15

define a systematic random sample

Answer 15

randomly select first person followed by every x^th person from the population is chosen

systematically choosing from the population by dividing the population size by the desired sample to determine the interval at which sample is selected

e.g. select a sample of 1000 from a list of 10,000&raquo_space; select every 10th person form the list

Question 16

what needs to be considered when using a systematic random sample

Answer 16

sampling bias

need to ensure list of elements/people is not arranged in a way that could lead to a biased sample (e.g. student list in GPA order)

Question 17

what is stratified sampling
and
when is it used

Answer 17

sampling by dividing the population in to subpopulations (strata) and randomly sample from the strata

if you want to make sure the profile of the sample matches the profile of the population on some important characteristics (e.g. ethnic mix, gender)

Question 18

why use stratified sampling?

Answer 18

can reduce sampling error by ensuring the ratios reflect the actual population (e.g. ratio of males to females(

to ensure that small subpopulations are included in the sample

Question 19

what is multistage cluster sampling?

Answer 19

begin with a sample of groupings then sampling individuals from said groupings

> larger sample obtained first to identify members of a subsample
randomly choose from sample to participate in the study

Question 20

wha is multistage cluster sampling good for?

Answer 20

identifying not readily identifiable sub groups

good but costly

Question 21

pros and cons of probability sampling

Answer 21

PRO
- helps to overcome sampling bias&raquo_space; representativeness

CON

choosing someone doesn’t mean they will take part

Question 22

define probability sampling

Answer 22

not every member of the population has an equal chance of being part of the sample

Question 23

when should Non-probability sampling be used

Answer 23

when there are no lists for the population of interest, no available (no sampling frame)

Question 24

what are the types of non-population sampling

Answer 24

convenience

snowball

Quota

purposive

Question 25

define convenience samples

Answer 25

selecting a sample from the available participants

e.g.
students enrolled in a particular course

people passing a particular location

Question 26

pros and cons of convenience samples

Answer 26

PRO
easy and inexpensive

CON
no control over representativeness

Question 27

define snowball sampling

Answer 27

collecting data with members of the population that can be located and then asking those members to provide information/contacts for other members of the population

Question 28

when is snowball sampling used?

Answer 28

used mainly for hard to study populations

e.g.
homeless young people

illegal immigrants

Question 29

what is a quota sample?

Answer 29

non probability sampling equivalent of stratified random sampling

want to reflect relative proportions of a population

without being able to sample randomly from each strata

Question 30

define purposive/judgement sampling

Answer 30

selection with a clear purpose to the sampling strategy
e.g. selecting key informants, atypical cases, deviant cases or a diversity of cases

> if unable to sample all of a population, choose groups most likely to have a rich data source

Question 31

when is purposive sampling used?

Answer 31

often used to

• select cases that might be especially informative
• select cases in a difficult to reach popluation
• select cases for in-depth investigation

Question 32

what are the 5 rules of determining sample size?

Answer 32

1. if population = <100, use entire population
2. larger sample sizes make it easier to detect an effect or relationship in a population
3. compare to other research studies in area through lit review
4. use a power table for a rough estimate
   use a sample size calculator