China Market Research - Sampling Method
Sampling method can be divided into
two types: Non probability sampling and probability sampling. Non
probability sampling does not follow the probability principal. It is based
on human's subjective experience or other conditions and is commonly used
for explorative research. Probability sampling involves the selection of a
sample from a population, based on the principle of randomization or chance.
Starmass International will design the sampling methods
scientifically and practicably in accordance with our clients requirements in
China market entry, purpose of China market research and characteristics of the selected market
Haphazard sampling is sometimes referred to as convenience or accidental
sampling. A haphazard sample is used by simply stopping anybody in the
street who is willing to answer the questions. In other words, the sample
comprises subjects who are simply available conveniently to the researcher.
The obvious advantage is that the method is that it is low in cost, saves time
and expenses. However, this advantage is greatly offset by the presence of
bias. Although useful applications of the technique are limited, it can
deliver accurate results when the population is homogeneous.
2. Judgement sampling
Selection of sample is based on certain judgement about the overall population.
The underlying assumption is that the investigator will select the subjects
according to the characteristic of the population. The accuracy of judgement
sampling will be affected by researcher's biases which may be more than
haphazard sampling. Biasness can be introduced if the researchers have their
own preconception regarding the research as they are reflected in the
sample. If these preconceptions are inaccurate, large biasness would occur.
3. Quota sampling
Sample units in the population do not have a known chance of selection in quota
sampling. Interviewers are required to find cases with similar
characteristics. A quota of particular types of people will need to be
interviewed. The information gathered will be organized and the final sample
would be representative of population.
4. Snowball sampling
Snowball sampling is a type of non-probability sampling where initial
respondents are selected at random and subsequent respondents are then
selected by referrals or information from the earlier respondents. The
selection of one element leads to the identification and selection of others
and these in turn to others, and so on like a rolling snowball which would
increase in size.
1. Simple random sampling
In simple random sampling, each member of a population has an equal chance of
being included in the sample. Also, each combination of members of the
population has an equal chance of composing the sample. This is the easiest
method of sampling and it is most commonly used. Advantages include no
requirements of any additional information on the frame other than the
complete list of members of the survey population along with information for
Using stratified sampling, the population is divided into homogeneous, mutually
exclusive groups called strata, and independent samples are then selected
from each stratum. Stratified sampling ensures an adequate sample size for
sub-groups in the population of interest. This method is a frequently used
method that is superior to random sampling because it reduces sampling
3. Cluster sampling
the population into clusters, a number of them will be randomly selected to
represent the total population except those in the non-selected clusters.
This method is low in cost and it is convenient as all units in the
population are not always available but a list of all clusters saves time.
4. Interval sampling
sampling is sometimes referred to as systematic sampling, it means that
there is a gap, or interval, between each selected unit in the sample, for
example, measuring depth in a stream every 50 meters or interviewing every
tenth person as part of a survey. The advantages of interval sampling in
China market research are
that the sample selection cannot be easier and that the sample is
distributed evenly over the listed population.
5. Multi-stage sampling
Multi-stage sampling, as the name
implies, involves drawing from several different samples. First, large
groups (includes more units that required) are selected. The process of
selecting population units within the groups continues until there is a
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