A KIND OF SAMPLING METHODS

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Pendidikan matematika regular 2007

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SAMPLING METHODS

In statistics, a sample is a subset of population. Typically, the population is very large, making a census or a completee numeration of all the values in the population impractical or impossible. The sample represents a subset of manageable size. Samples are collected and statistics are calculated from the samples so that one can make inferences or extrapolations from the sample to the population. This process of collecting information from a sample is referred to as sampling. from wikipedia

Sampling is the process of selecting units (e.g., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to the population from which they were chosen. Let's begin by covering some of the key terms in sampling like "population" and "sampling frame." Then, because some types of sampling rely upon quantitative models, we'll talk about some of the statistical terms used in sampling. Finally, we'll discuss the major distinction between probability and non-probability sampling methods and work through the major types in each. from : socialresearchmethods com

Sampling is choosing which subjects to measure in a research project. Usually the subjects are people, but subjects could also be organizations, cities, even nations. Measurement is typically accomplished through survey instruments, but could also be by observation, archival record, or other method. Regardless, sampling will determine how much and how well the researcher may generalize his or her findings. A bad sample may well render findings meaningless.

(http://faculty.chass.ncsu.edu/garson/PA765/sampling.htm)

SAMPLING METHODS

a. Random Sampling

A random sample is one chosen by a method involving an unpredictable component. Random sampling can also refer to taking a number of independent observations from the same probability distribution, without involving any real population. A probability sample is one in which each item has a known probability of being in the sample. The sample usually will not be completely representative of the population from which it was drawn— this random variation in the results is known as sampling error. In the case of random samples, mathematical theory is available to assess the sampling error. Thus, estimates obtained from random samples can be accompanied by measures of the uncertainty associated with the estimate. This can take the form of a standard error, or if the sample is large enough for the central limit theorem to take effect, confidence intervals may be calculated. Random sampling- all members of the population have an equal chance of being selected as part of the sample. You might think this means just standing in the street and asking passers-by to answer your questions. However, there would be many members of the population who would not be in the street at the time you are there, therefore, they do not stand any chance of being part of your sample. To pick a random sample, it is necessary to take all the names on the electoral register( a list of all the people who live in a particular area) and pick out, for example, every fiftieth name. This particular person needs to be interviewed to make the sample truly random. Random sampling is very expensive and time consuming, but gives a true sample of the population. from wikipedia

b. Systematic Sampling

A method of selecting sample members from a larger population according to a random starting point and a fixed, periodic interval. Typically, every "nth" member is selected from the total population for inclusion in the sample population. Systematic sampling is still thought of as being random, as long as the periodic interval is determined beforehand and the starting point is random. A common way of selecting members for a sample population using systematic sampling is simply to divide the total number of units in the general population by the desired number of units for the sample population. The result of the division serves as the marker for selecting sample units from within the general population. For example, if you wanted to select a random group of 1,000 people from a population of 50,000 using systematic sampling, you would simply select every 50th person, since 50,000/1,000 = 50. from investopedia

c. Stratified Sampling

Definition: There may often be factors which divide up the population into sub-populations (groups / strata) and we may expect the measurement of interest to vary among the different sub-populations. This has to be accounted for when we select a sample from the population in order that we obtain a sample that is representative of the population. This is achieved by stratified sampling. A stratified sample is obtained by taking samples from each stratum or sub-group of a population.

(http://www.bized.co.uk/cgi-bin/glossarydb/browse.pl?glosid=1322)

d. Convenience Sampling

A convenience sample is a sample where the patients are selected, in part or in whole, at the convenience of the researcher. The researcher makes no attempt, or only a limited attempt, to insure that this sample is an accurate representation of some larger group or population. The classic example of a convenience sample is standing at a shopping mall and selecting shoppers as they walk by to fill out a survey. In contrast, a random sample is one where the researcher insures (usually through the use of random numbers applied to a list of the entire population) that each member of that population has an equal probability of being selected. Random samples are an important foundation of Statistics. Almost all of the mathematical theory upon which Statistics are based rely on assumptions which are consistent with a random sample. This theory is inconsistent with data collected from a convenience sample. In general, the Statistics community frowns on convenience samples. You will often have great difficulty in generalizing the results of a convenience sample to any population that has practical relevance. from : childreenmercy

e. Judgment Sampling

Judgement sampling involves the choice of subjects who are most advantageously placed or in the best position to provide the information required. For instance, if a researcher wants to find out what it takes for women managers to make it to the top, the only people who can give first hand information re the women? Who have risen to the positions of presidents, vice presidents and important top-level executives in work organizations? They could reasonably be expected to have expert knowledge by virtue of having gone through the experience and processes themselves and might perhaps be able to provide good data or information to the researcher. Thus the judgement sampling design is used when a limited number or category of people have the information that is sought. In such cases any type of probability sampling across a cross-section of the entire population is purposeless and not useful. Judgement sampling may curtail the generalizability of the finding due to the fact that we are using a sample of experts who are conveniently available to us. However it is the only viable sampling method for obtaining the type of information that is required from very specific pockets of people who are very knowledgeable are included in the sample. from : blurtit

f. Quota Sampling

Quota sampling is often used in market research because it does not require a list of potential respondents (a 'sampling frame'). It is not based on random selection. Instead, respondents who fit into predetermined categories ('quota controls') are found by interviewers until their quotas are filled. For this survey, the quota controls to be used are sex and age (young, middle, and old).

A recent census has reported that there are:

5252 males

5789 females

2940 young

3921 middle aged

4180 old

in the town. You should choose the numbers in your sample in each category so that they are approximately representative of the town as a whole.

(http://www.soc.surrey.ac.uk/samp/quota.php)

g. Snowball Sampling

With this approach, you initially contact a few potential respondents and then ask them whether they know of anybody with the same characteristics that you are looking for in your research. For example, if you wanted to interview a sample of vegetarians / cyclists / people with a particular disability / people who support a particular political party etc., your initial contacts may well have knowledge (through e.g. support group) of others. from : tardis.ed.ac

According the explanation above we have some sampling methods. There are random sampling, stratified sampling, quota sampling, snowball sampling, judgment sampling, and convenience sampling.