wk 2

Question 1

quantitative research

Answer 1

objective
generates ‘facts’ about human behaviour
aims to explain the data and generate predictions
ideally requires LARGE PROBABILISTIC SAMPLES
uses statistical tests to process numerical data
seeks to discover general laws governing human behaviour -> nomothetic approach
associated with realism

Question 2

qualitative research

Answer 2

subjective
uncovering the meaning ascribed to individual behaviour
aims to describe the data and generate understanding
often relies on SMALL NON-PROBABILISTIC SAMPLES
uses analytic and conceptual tools as well as data extracts to produce compelling arguments
interested in unique (idiosyncratic) features of single individuals -> idiographic
associated with interpretativism, constructivism and realism

Question 3

probability sampling

Answer 3

requires each unit in the population to have a KNOWN CHANCE to be selected.
requires a clearly defined population that we can access

Question 4

types of probability sampling

Answer 4

simple random
systematic random
stratified
cluster
multi stage

Question 5

simple random

Answer 5

each unit has a known and equal chance of being selected.
samples are selected at random using a technique :
lottery method / hat method / table of random numbers

Question 6

systematic sampling

Answer 6

each unit in a population has a known and equal chance of being selected
samples are selected systematically -> everything Nth unit is selected
✔️ work without a population list if population availability is not an issue
✖️ distribution of the population frame needs to be random
✖️ both simple and systematic random sampling do not yield by default representative samples

Question 7

stratified

Answer 7

introduces a step before sampling the population to determine the sub-groups.
proportionate / disproportionate stratified sampling depending on whether we apply the same sampling fraction across the sub-groups
✔️ more representative
✖️ all these echinacea can be very time consuming and costly

Question 8

cluster

Answer 8

selecting clusters that reduce time and costs for accessing sampling units
clustering : only elements in te selected clusters are samples
stratified : elements from all groups are sampled

Question 9

multi stage

Answer 9

applying random or systematic sampling at several stages of constituting the sample
random selection of one group and further randomising that group.

Question 10

non probability sampling

Answer 10

the chance for each unit in the population to be selected is NOT KNOWN.
list of units in population is not needed.
used in experimental research

Question 11

types of non-probabilistic sampling

Answer 11

convenience
purposive
quota
snowball

Question 12

convenience

Answer 12

(availability / ad libitum)
participants who are available to the researcher - respond to an ad or volunteer
most common

Question 13

purposive

Answer 13

people who have a particular set of characteristics that are relevant for the study

Question 14

quota

Answer 14

more representative
an extra step before unit selection / identifying relevant characteristics of the units and the % in the population
apply convenience sampling to fill the quotas

Question 15

snowball

Answer 15

small/ hard to reach populations with specific characteristics
when serveral sample units are identified we ask each individual to refer a fixed number of persons that fit our selection criteria

ptps recruit new ptps
✔️ reaches hidden populations
✖️ initial individuals will bias the sample

Question 16

sampling bias

Answer 16

effects external validity and representativity

Question 17

no response bias

Answer 17

lead to non-representative sample

Question 18

WEIRD participants

Answer 18

Western
Educated
Industrialised
Rich
Democratic