Module 7 - Sampling in quantitative research

Question 1

Sampling

Answer 1

Collecting data from a selection of
cases from the population.

Question 2

Sample

Answer 2

The selected cases.

Question 3

Population

Answer 3

The whole
group of cases (or “units of analysis”) about which
you want to generalize, make general claims.

Question 4

Sampling fraction

Answer 4

Which percentage of the
population are you going to select for your sample?

Question 5

Sampling error

Answer 5

Bias due to differences between the whole population and a random sample from that population.

Question 6

Sampling frame

Answer 6

The list of all units in the
population

Question 7

Sampling bias

Answer 7

Distortion of representativeness because some units have a higher chance to be selected than others

Question 8

Response rate

Answer 8

The proportion of selected people
who actually participate in the study

Question 9

Non-response bias

Answer 9

Differences between
participants and non-participants.

Question 10

Representativeness of a sample

Answer 10

to what extent do the
characteristics of the units in the sample and the population differ?

Question 11

Probability sample

Answer 11

Each element (person, unit,
case) in the population has a certain, known chance
to be selected for the sampl

Question 12

Random sample

Answer 12

Each element has the same chance of
being selected

Question 13

Nonprobability sample

Answer 13

the chance is unknown;
it is impossible to calculate the chance.

Question 14

Simple random sampling

Answer 14

Give all elements in your sampling frame a number and subsequently some numbers are drawn randomly.

Question 15

Systematic sampling

Answer 15

Example:
* You have a list with 1,000 addresses, and you want
a sample of 100 addresses.
* This means you need 10% (sampling fraction): 1
address out of every 10 addresses.
* Choice a random number from 1-10.
* Suppose this number turns out to be 3 → select
address 3, 13, 23, 33, 43 etc.

Question 16

Stratified random sampling

Answer 16

Suitable when the population consists of different
groups (strata) that…
– Differ from each other.
– Are internally relatively homogeneous.
* In this case, you could:
– Divide the population in groups.
– Draw simple random samples of each group.