What is stratified cluster sampling?

Stratified sampling, also known as type sampling. It is to divide the whole unit into several types or levels according to its attribute characteristics, and then randomly select sample units from these types or levels. Sampling characteristics

What is stratified sampling? The characteristics are: due to classification and stratification, the similarity between various types of units increases, and it is easy to extract representative survey samples. This method is suitable for situations where the overall situation is complex, there are large differences between units and there are many units.

[Edit] Method for determining the number of samples in each layer

Market research methods

A

Desk research

Case study method

B

Non-repeated sampling

C

Random surprise inspection

Reset sampling

draw lots

Product lien test

D

Multidimensional scaling method

Quantitative research methods

Qualitative research methods

Typical investigation method

Telephone survey

Multistage sampling

Equidistant sampling

Independent control quota sampling

Equidistant scale

Equidistant scale

E

Second-hand data survey

Two-way focus group

F

Non-probabilistic sampling

group sampling

Stratified proportional sampling

Hierarchical optimal sampling

G

Observation method

probability sampling

Inflection point investigation

Si Nuo Bao Samplin

H

Conference survey

J

Focus interview method

Empirical judgment method

random sampling

Family diary method

Dealer interview

K

feasibility study

Control experiment method

L

Joint analysis method

Lien investigation

Garbage investigation method

Category scale

M

Interview method

Blind text

Descriptive investigation

Media investigation method

P

Postscript

Judgement sample

Quota sampling

Balance method

Evaluation scale

paired comparison scales

Q

Q classification

rare

random sampling

S

volumetric method

Structural equation modeling

personal interview

Multiple sampling

Experimental research methods

Field research

Digital distribution scale

Random number table method

Order size

T

projection technique

Promotion estimation method

Projection research

exploratory research

W

Literature investigation method

Questionnaire survey method

Network research

Desk research survey

An unprepared visit

online research

X

Query method

Syndicate research

trace analysis

Mutual control quota sampling

Y

Mail survey

Causality investigation

Z

Subjective probability method

Nested sampling method

Major investigation

Door-to-door search method

[edit]

There are three ways to determine the number of samples in each layer:

(1) Stratification ratio. That is to say, the ratio of the number of samples in each layer to the total number of layers is equal. For example, if the sample size n=50 and the population N=500, then n/N=0. 1 is the sample ratio, and the number of samples in each layer is determined according to this ratio.

② Naiman method. That is to say, the number of samples to be sampled in each layer is directly proportional to the product of the total number of the layer and its standard deviation.

③ Non-proportional distribution method. When the number of cases at a certain level is too small in the total, in order to fully reflect the characteristics of this level in the sample, the proportion of the number of samples at this level in the total sample can be artificially and appropriately increased. But doing so will increase the complexity of reasoning.