Sampling In Research
INTRODUCTION
What is a sample?
A sample is a finite part of a statistical population whose properties are studied to gain information about the whole(Webster, 1985). When dealing with people, it can be defined as a set of respondents(people) selected from a larger population for the purpose of a survey.A population is a group of individuals persons, objects, or items from which samples are taken for measurement for example a population of presidents or professors, books or students.
What is sampling? Sampling is the act, process, or technique of selecting a suitable sample, or a representative part of a population for the purpose of determining parameters or characteristics of the whole population.
What is the purpose of sampling? To draw conclusions about populations from samples, we must use inferential statistics which enables us to determine a population`s characteristics by directly observing only a portion (or sample) of the population. We obtain a sample rather than a complete enumeration (a census ) of the population for many reasons. Obviously, it is cheaper to observe a part rather than the whole, but we should prepare ourselves to cope with the dangers of using samples. In this tutorial, we will investigate various kinds of sampling procedures. Some are better than others but all may yield samples that are inaccurate and unreliable. We will learn how to minimize these dangers, but some potential error is the price we must pay for the convenience and savings the samples provide.There would be no need for statistical theory if a census rather than a sample was always used to obtain information about populations. But a census may not be practical and is almost never economical. There are six main reasons for sampling instead of doing a census. These are; -Economy -Timeliness -The large size of many populations -Inaccessibility of some of the population -Destructiveness of the observation -accuracy
The economic advantage of using a sample in research Obviously, taking a sample requires fewer resources than a census. For example, let us assume that you are one of the very curious students around. You have heard so much about SJU and now that you are there, you want to hear from the insiders. You want to know what all the students at SJU think about the quality of teaching they receive, you know that all the students are different so they are likely to have different perceptions and you believe you must get all these perceptions so you decide because you want an indepth view of every student, you will conduct personal interviews with each one of them and you want the results in 20 days only, let us assume this particular time you are doing your research SJU has only 20,000 students and those who are helping are so fast at the interviewing art that together you can interview at least 10 students per person per day in addition to your 18 credit hours of course work. You will require 100 research assistants for 20 days and since you are paying them minimum wage of $5.00 per hour for ten hours ($50.00) per person per day, you will require $100000.00 just to complete the interviews, analysis will just be impossible. You may decide to hire additional assistants to help with the analysis at another $100000.00 and so on assuming you have that amount on your account.
As unrealistic as this example is, it does illustrate the very high cost of census. For the type of information desired, a small wisely selected sample of SJU students can serve the purpose. You don`t even have to hire a single assistant. You can complete the interviews and analysis on your own. Rarely does a circustance require a census of the population, and even more rarely does one justify the expense.
The time factor.
A sample may provide you with needed information quickly. For example, you are a Doctor and a disease has broken out in a village within your area of jurisdiction, the disease is contagious and it is killing within hours nobody knows what it is. You are required to conduct quick tests to help save the situation. If you try a census of those affected, they may be long dead when you arrive with your results. In such a case just a few of those already infected could be used to provide the required information.The very large populations
Many populations about which inferences must be made are quite large. For example, Consider the population of high school seniors in United States of America, agroup numbering 4,000,000. The responsible agency in the government has to plan for how they will be absorbed into the differnt departments and even the private sector. The employers would like to have specific knowledge about the student`s plans in order to make compatiple plans to absorb them during the coming year. But the big size of the population makes it physically impossible to conduct a census. In such a case, selecting a representative sample may be the only way to get the information required from high school seniors.The partly accessible populations
There are Some populations that are so difficult to get access to that only a sample can be used. Like people in prison, like crashed aeroplanes in the deep seas, presidents e.t.c. The inaccessibility may be economic or time related. Like a particular study population may be so costly to reach like the population of planets that only a sample can be used. In other cases, a population of some events may be taking too long to occur that only sample information can be relied on. For example natural disasters like a flood that occurs every 100 years or take the example of the flood that occured in Noah`s days. It has never occured again.The destructive nature of the observation Sometimes the very act of observing the desired charecteristic of a unit of the population destroys it for the intended use. Good examples of this occur in quality control. For example to test the quality of a fuse, to determine whether it is defective, it must be destroyed. To obtain a census of the quality of a lorry load of fuses, you have to destroy all of them. This is contrary to the purpose served by quality-control testing. In this case, only a sample should be used to assess the quality of the fuses
Accuracy and sampling A sample may be more accurate than a census. A sloppily conducted census can
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Chapisha Maoni