The selection of a sample is a fundamental activity in survey and experimental research. A phenomenological study will require a sample of one subject. A sample is a subset of a population. A population may refer to a body of people or collection of items under consideration for a given research purpose. A sampling frame refers to a list of other records of the population from which all the
sampling units are drawn. This is sometimes called the sample space. In a large business organisation, for example, you may have a list of all the employees and this forms the sample frame or space from which you can obtain a sample of employees in the organisation. Statisticians use sample behaviours to draw inferences about the population behaviour. Figure 3.3 illustrate the difference between a sample and a population
Figure 3.3: Pictorial Representation of the Difference Between Population and Sample.
--- Population .
Sample
At times, you may want to use the entire population instead of a sample. This decision
will depend on the size of your study as well as the size of your population of interest. If your research topic is concerned with the performance of small- and medium-scale
beverage companies at Enugu State, for example, you may decide, for purpose of the research, that you will solely focus on a company with a turnover of less than N200
million per year. You will need to identify companies that fit this criteria. If your investigations indicate that there are 20 such companies in the state, your research findings will relate only to beverage companies in Enugu State.
A good and representative sample for the entire population is one in which the results obtained from the sample can be taken to be true for the entire population. It is the one in which you can generalise from the results. In scientific research, it has been said that a good sample must be:
1. Chosen at random that is, every member of the population must have a chance of being selected
2. Large enough to satisfy the needs of the investigation being undertaken 3. Unbiased.
You must make sure that your sample is not biased and is representative of the population from which it is drawn. A situation where you can have a biased sample is where you ask for volunteers to participate in the study or where you select your friends. This sample is likely to be biased as the volunteers or friends may possess certain
characteristics that those who do not volunteer do not have. A good sample selection involves the following activities, shown in figure 3.4 below.
Figure 3.4: Selecting a Sample Define target population
Obtain or construct the sample frame or space
Determine how you will select the members of the sample
Decide how to convert sample estimates into population estimates
3.5 Self -Assessment Exercise
Explain what you understand by the following:
(a) A variable (b) A sample (c) A population
4.0 Conclusion
You have been informed in this unit that data collection is a very critical and expensive activity in a research project. Associated with data collection is sampling for which if wrongly done can make generalisation of findings invalid and unacceptable.
Also in this unit, you are able to identify the various types of variables, with the basic classifications being dependent and independent variable. Variables can also be classified as either qualitative or quantitative variable.
5.0 Sum mary
The different possible methods of data collection has been listed as:
1. The critical incident method, widely used during in-depth interviews to generate qualitative data.
2. Diaries, a daily record of events or thoughts used in capturing what people do, think and feel.
3. Focus group method, normally associated with a phenomenological methodology and used to gather data relating to the feelings and opinions of a group of people involved in a common situation
4. Interview method 5. Observation method
6. Protocol analysis, used in ascertaining the way people behave and think in a given situation.
7. Questionnaires method
When you use a method to collect data on the frequency of occurrence of a phenomenon or variable, you will obtain quantitative data. But if you are collecting data on the meaning of a phenomenon, you will obtain a qualitative data. Quantitative data is referred to as numerical data while qualitative data is referred to as nominal data.
Researchers are interested in collecting data about variables. The most important
characteristic of a variable has been identified as its ability to change; a variable can take more than one value, either across entities (for cross-section data) or within the same entity over time (for time-series data). These different values can be observed and measured in the research process.
A variable can either be qualitative or quantitative. A qualitative variable can be referred to as a non-numerical attribute of an individual or object.
referred to as a numerical attribute of an individual or object.
A quantitative variable can be
An independent variable is the variable that can be manipulated in order to be able to predict the values of the dependent variable. A dependent variable is the variable whose values are being predicted by the independent variable.
A good and representative sample for the entire population is one in which the results obtained from the sample can be taken to be true for the entire population. A good sample must be:
1. Chosen at random that is, every member of the population must have a chance of being selected
2. Large enough to satisfy the needs of the investigation being undertaken 3. Unbiased.
6.0 Tutor-Marked Assignm ent
Explain why it is important for your sample to be unbiased.
7.0 References
Hussey, J. and Hussey, R. (1997) Business Research: A Practical Guide for Undergraduate and Postgraduate Students (New York: Palgrave).
UNIT 8: SAMPLING DESIGN AND DETERMINATION OF THE