In the quantitative research, we know about the population and sample. What is the definition? and How to calculate it? Here I will share about the terms are. Read carefully!
Population is the total number of units of analysis whose characteristics will be studied. The population is divided into two, namely:
- Population sampling, for example, if we take as a sample of households, while the investigation was a member of the household who work as civil servants, the entire household is the sampling population.
- The target population, in accordance with the above example, all civil servants are the target population.
The sample is part of a population that is expected to represent the population in the study. In the preparation of the sample needs to be compiled a sampling frame is a list of all the elements of the sampling in the sampling population, provided that:
- Should include all elements of the sample
- No element of samples counted twice
- Must be up to date
- Limits must be clear
- Must be traceable to the field
According to Teken (in Masri Singarimbun and Sofyan Efendi) The characteristics of the ideal sample is:
- Can produce a credible result which represents the entire population studied
- Can specify precision of the results of research to determine the standard deviation of estimates obtained
- Simple, so easy to implement.
- Can provide as much information as possible at low cost.
There are four factors that must be considered in determining the size of the sample, among others:
- Degree of homogenity of the population, the more homogeneous population of fewer number of samples taken
- Precision desired, the higher the desired level of precision that the more the number of samples taken
- Analysis plan
- Costs and time
3. Some Techniques in Sampling
There are several techniques in sampling, but it can be divided into two parts, those are:
a. Probability sampling or random sampling
- Simple random sampling, simple random sampling, a sample is taken so that each research unit or unit element of the population has an equal opportunity to be selected into the sample. The method used by (1) the lottery, (2) ordinal (number multiples), (3) a table of random numbers
- Proportionate stratified random sampling, for example by students as a sample, ... it is necessary to calcification of students based strata (e.g, class I, II and III)
- Disproportional stratified random sampling
- Area Sampling, sample retrieval technique based on region
- Cluster sampling, sampling techniques based cluster or clusters, for example: a study wanted to know the family income in a village, with a variety of clusters, eg in terms of jobs: Farmers, Workers, civil servants, Fishermen
b. Non-Probability Sampling
Non probability sampling consists of:
- Systematic sampling, ie selecting a sample from an order of the list according to a specific order, eg, each individual sequence of no n-th (10, 15, 20 etc.)
- Sampling quota (quota sampling), sampling techniques are based on the fulfillment of the desired sample amount (determined)
- Accidental sampling, samples taken from anyone who happened to be, for example, by asking anyone who found the street ... to ask for opinions about the rise in food prices
- Purposive sampling, sampling techniques based won upon a particular purpose. (people who have been truly have the criteria as a sample)
- Sampling saturated (census),
- Snowball sampling, starting from a small group who were asked to show their friends. The friend then asked to show his friends again and so on until sufficiently.
4. Sample Size Determination Techniques
One way to determine the number of samples is using the formula of Taro Yamane:
n = number of samples,
N = Total Population,
d² = precision required (eg 5% or 10%)
Population is total or the amount of subject while sample is part of population which represent the subject of research. Please, studying more about this two terms in two big approach (quantitative and qualitative research) because there are some differences on that case. Thanks.
Read also: Sampling Techniques
Read also: Sampling Techniques