topic 5 sampling

Question 1

When do we need sampling?

Answer 1

• If not all units mentioned in our research question can be studied, we need “sample”
• Sample is a subset of the units of analysis
• That implies: Studying a smaller set of units with the aim to say something about all units

Question 2

what does sampling imply

Answer 2

• That implies: Studying a smaller set of units with the aim to say something about all units

Question 3

Sampling process:

Answer 3

population, Sampling frame, Sample,Interviewed sample, Data

Question 4

The relationship between sampling frame and sample

Answer 4

sampling

Question 5

where and what type of errors may occur

Answer 5

between sampling frame and sample, Might be disturbed by sampling error & bias.

Question 6

what can. occur Between population and sampling frame

Answer 6

might be registration errors (list is incomplete), RECORDING OR REGISTRATING DATA

Question 7

relationship between sample and interviewed sample

Answer 7

non response, refusals

Question 8

Non-Response Rate:

Answer 8

The non-response rate is the percentage of selected individuals in a sample who do not participate or provide data in a study. It can introduce bias if non-respondents differ systematically from respondents in ways that affect the study’s results.

Question 9

Response Rate

Answer 9

INTERVIEWED SAMPLE UP AND SAMPLE SIZE DOWN The response rate is the percentage of selected individuals in a sample who participate and provide data in a study. A higher response rate generally leads to more representative and reliable results. Researchers often aim to maximize response rates to minimize the potential for bias.

Question 10

TWO TYPES OF SAMPLING

Answer 10

probabibilty and non probab

Question 11

Probability sampling

Answer 11

If the probability (chance) is known, that a specific unit of the sampling frame is included in the study. The sample is not biased
- Allows for geralizations to larger population
- Sampling Methods:

Question 12

Simple random Sampling

Answer 12

In simple sampling, every member of the population has an equal chance of being selected for the sample. It’s like drawing names from a hat with no regard for specific characteristics.

Question 13

Stratified Sampling

Answer 13

In stratified sampling, the population is divided into subgroups or strata based on certain characteristics (e.g., age, gender), and then random samples are taken from each subgroup. This method ensures representation from each subgroup.

Question 14

Cluster Sampling (or Multi-Stage Cluster Sampling):

Answer 14

In cluster sampling, the population is divided into clusters or groups, often based on geographic regions. A random sample of clusters is selected, and then all individuals within those selected clusters are included in the sample. This method is practical when it’s difficult to reach every individual in the population directly.

Question 15

Non-probability sampling

Answer 15

not all have the same chance, If the probability (chance) is not known, that a specific unit of the sampling frame is included in the study reflect the population. The sample is probably biased (voreingenommen).
- Does not allow for generalizations to a larger population of units
- Non-probability sampling methods:

Question 16

Purposive sampling:

Answer 16

most USEFUL representatives,, based on researchers judgement, a type of nonprobability sampling in which the units to be observed are selected on the basis of the researcher’s judgment about which ones will be the most useful or representative.

Question 17

Snowball sampling

Answer 17

often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing.

Question 18

why snowball

Answer 18

hard to reach a certain group

Question 19

Quota sampling

Answer 19

fit the characteristics, units are selected for a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied

Question 20

informant

Answer 20

someone who is educated on the subject and is willing to provide us with info

Question 21

element

Answer 21

basic unit, individual, unit of population

Question 22

population

Answer 22

certain group of individuals that is studied

Question 23

random selection

Answer 23

equal chance

Question 24

sampling unit

Answer 24

the individual element or group of elements considered for selection the sampling process

Question 25

parametr

Answer 25

certain characteristics

Question 26

representatives

Answer 26

the degree to which a sample is accurately reflecting the characteristics of the pop

Question 27

sampling errors

Answer 27

bias or sampling error

Question 28

sampling bias

Answer 28

sample is not selected randomly, groups being over represented

Question 29

sampling error

Answer 29

Sampling error refers to the variation that arises when the characteristics of a sample do not perfectly match those of the overall population from which it is taken