Sunday, July 1, 2012

Population and sample in Polling

A study has a component that can not be separated from the research itself. Component is called the population and sample. Two things can be interpreted as simple. Population can be used to refer to all the elements in the research area. Generalized areas such as object or subject is determined by a researcher to be used as research material to be learned. From the results of research and learning is then found to be the conclusion. All things are about to study its characteristics will be estimated.

Associated with the population and sample, the population has two kinds of characters, namely homogeneous and heterogeneous populations. Homogeneous population is the population of individuals in it can be likened to the relative chances of being sampled and otherwise heterogeneous population. The characteristics that have a population can be considered as a parameter.

The set of objects of research could consist of a set of people or objects. This included the set of objects in the form of such an individual, group, community, society, and so forth. While the form of objects such as the number of vehicles, buildings, locations, and so forth. Collection or set of persons (objects) are studied usually have in common in one or more of the principal and can lead to problems in a study. Before conducting the study, the population in the understanding of population and the sample to be studied first to be defined clearly.

Associated with the population and sample, of course, we also must know the name of the sample. The sample becomes important when we will clarify the focus of research. Sample including part of the elements of the population and may represent the entire population is a subject of research. Samples can also be described as a miniature of the population. Sample there is any kind, in terms of traits or characteristics, that the sample is representative and characteristic of known statistical characteristics. The next question that must be understood: Why should there be sampling ? The answer is because the population and sample, which has a population of large quantities and should be more specific. Because, would be very difficult to examine all relevant elements. This is because it would blur the focus of research.

Accordingly, there is also the problem of time constraints, costs, and human resources. Research on the sample can be more reliable than in the population. This is because the data is too much will make the physical and mental health are becoming increasingly tired. Thus, likely to be too complex and obscure the focus of research. Therefore, the presence of significant samples in the population and a study. The substance of sampling aims to obtain a representative population of the right, at least have a validity that can be trusted. Consideration the characteristics of the population will determine the sampling technique. This is in order to minimize the bias associated with the temporary ability to estimate the precision in the population and sample, so that later can be generalized over the population.

In connection with this matter before the sample must have a characteristic that belongs to the population. Also has two types of samples in its application, ie a probability sample and the sample nonprobabilitas. The probability is homogeneous and has the number of sampling models, the sample random sampling, stratified random sampling, proportionate stratified radom sampling, cluster sampling or sample groups.

In addition, there are samples that are heterogeneous nonprobabilitas also has several sampling models, the systematic sampling, quota sampling convenience sampling, sampling purposeive, boring sampling or total sampling is typically used for a population less than one hundred people.Taking the example of Population and Sample Associated with the population and sample, sampling of the population has a lot of formulas. One of these samples to determine the Slovin formula. This formula can be used as an example of the work and the sample population.
Slovin formula: n = N / 1 + (N x e2)

Description :
  • n = the sample members
  • N = Number of population
  • e = error level. Generally 1% or 5% and 10%

For example : The number of population or N is 200, and e is the error level or 5%. Then the number of samples is as follows. n = 200/1 + (200 x 5%) = 133, 33 or rounded up to 133 people. In addition, there are other examples.

The example below is taken from a poll of the country in Yogyakarta campus bulletin. This bulletin is holding a poll on how students respond to the separation of the faculty into two faculties. However, the sample and the population here combined with data analysis in which exposure to the poll have been shaped and can be seen how the transparency of the population and sample.

In addition, the method of calculation is notified to the reader so that polling can be considered valid and have the data and calculations are more transparent.Implementation example - FE Student Support Inauguration. The absence of a decision letter from Indonesia's Ministry of Education to make its own UNY not be sure when the Faculty of Economics (FE) will be unveiled. Faculty development is widely regarded as a hasty decision because the preparation of the building was not yet up to 80%.

Students study program (Prodi) that goes into the FE restless with uncertainty. Coupled with the issue of difficulty finding a job that circulated among students. How do student-related issues are there ? To find out, Tim Research Bulletin poll conducted expeditions. The method used is a quantitative type of stratified probability. Population and in the polling sample is composed of FE student population of 3491 candidates, 360 obtained a sample of students. Sample calculation using the Slovin formula with sample error of 5%.

Questionnaire distributed by a formula calculation of heterogeneous populations because the number of students in each study program varies. In this poll, through populations and samples that have been mentioned, there are two questions and four written statements in a questionnaire. Of questions or do not know about the formation of FE, 87%, of respondents answered yes and 12.4% were answered do not know. Most of those who answered do not know is a student of the semester I. Those new students who may not know much about the issue of FE. The next question is they agree with FE formation. The result, most of the respondents answered yes, they are confused by their own faculty status.

Students actually do not mind the status of their study program is incorporated in the Faculty of Social Sciences and Economics (FISE). 44.8% agreed, 9% strongly agreed, 18.6% disagree, 21.4% strongly disagreed, and the rest is in doubt. Even so, they state as much as 33.1% agree or strongly agree 24.1%, 17.2% disagree, strongly disagree 11%, 14.5% doubtful, and the remainder did not respond to their statements because of confusion with faculty status between FISE or is the FE.

The next statement, 37.3% agreed to launch more quickly FE, 37.2% strongly agree, 4.8% disagreed, 8.3% strongly disagreed, and 12.4% in doubt. Students did not mind the current status prodinya, but still want a faster opening of FE. Because most of them are worried if after graduation will have difficulty in getting a job because the status is still FISE Prodi.

This shows students FISE own panic because there is a worry because it is difficult to say when it is separated into two faculties. But, nonetheless agreed to separate, with separate faculty but will repeat some of the study program accreditation process.

1. Do you agree with the establishment of the Faculty of Economics UNY separated from the Faculty of Social Sciences and Economics?
  • Yes = 81.4%
  • No = 15.8%
  • Not responding = 2.8%

2. You feel anxious when after graduation will be difficult to get a job because of the status of the study program is still in the FISE.
  • Strongly disagree = 16.6%
  • Do not agree = 19.3%
  • In doubt = 19.3%
  • Agree = 22%
  • Strongly agree = 22.8%
Through this example, you can do a poll in the same way or with different sampling methods. Points 1 and 2 above can be made into an image in order to attract readers to facilitate the reading of data. Population and the sample can only become more complicated as the size of the population which is the object of research was the study population and sample processing.

Therefore, as often practiced using sampling methods in a simple poll will improve the ability to calculate the population more and make us more understanding about how the population and sample, both functionally and structurally to the reality of how their application. Good luck.

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