Before you embark on your fieldwork, you need to decide on who and what you want to sample to define the scope of your research. You should discuss and think through how many tourists or which part of Chinatown you want to cover in your on-site field study.
What is sampling?
A process used in statistical analysis in which a predetermined number of observations will be taken from a larger population. The methodology used to sample from a larger population will depend on the type of analysis being performed, but will include simple random sampling, systematic sampling and observational sampling.
The sample should be a representation of the general population.
(http://www.answers.com/topic/sampling#ixzz1Kbez4NBm)
Why sample?
It is impossible and unnecessary for you to interview all the tourists you see or spend too much time in Chinatown to collect your data. Sampling allows you to complete your research faster and at a lower cost. A good sample allows you an accurate investigation of Chinatown in a feasible and practical way without having to study the whole Chinatown.
How to sample?
a) Avoid bias when designing the sampling frame and time
b) Choose a representative sample across different ages, gender and any other relevant factors.
c) Avoid very small sample sizes (50-200 is an ideal and manageable size)
Your team and teachers will have to define the scope of your investigation together based on your inquiry question. You have to bear in mind the timeline and resources you have been given before you decide on who, where and what to sample in your Chinatown fieldwork. You will also have to decide on which type of sampling method you want to adopt so that it is most useful and relevant for your field study.
Types of Sampling
Random sampling - respondent selected based on a random number table.
(You can use this formula in excel =INT(50*RAND())+1 in which 50 is the sample size and you can change the number to any other sample size).
Advantage of random sampling:
No human bias in selection.
Every person has an equal chance of being selected.
This can be used for large population.
It is quick and simple to administer
Disadvantage of random sampling:
When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased.
Results may be completely random and not representative e.g. only females are picked when the random number is drawn.
Systematic sampling - After the required sample size has been calculated, every Nth respondent is selected from a list of population members. The respondent can be regularly numbered, for example every 10th person.
Advantages of systematic sampling:
It provides more complete coverage of an area.
It is quick and no need to refer to random table.
Disadvantage of systematic sampling:
It is more biased, as not all members or points have an equal chance of being selected and that it may therefore lead to over or under representation.
There may be unrepresentative sample e.g. you ask every 10th person turns out to be female.
o Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers. The relevant stratums and their actual representation in the population is first identified. The population can be divided into known groups, and each group sampled using a random or systematic approach.
For example, in conducting a survey to compare the reasons for visiting Chinatown between tourists from Asian and non-Asian countries, a stratified sampling can be used where equal numbers of Asian and non-Asian tourists are selected.
To do this, the first question in the list of questions should be to ask for the country of origin of the tourist. They can ask the selected tourists for the main reason that the tourists are visiting Chinatown and see if there are any similarities or differences in their answers.
Advantages of stratified sampling:
· It can be used with random or systematic sampling.
· If the proportions of the sub-sets are known, it can generate results which are more representative of the whole population
· Correlations and comparisons can be made between sub-sets
o Disadvantages of stratified sampling:
· The proportions of the sub-sets must be known and accurate if it is to work properly,
· Time-consuming as the subcategories have to be identified and proportions calculated / may not have sufficient respondents for each subcategory.