An abstract is a mini-version of your work; paper, project, thesis or dissertation. It should cover the main objectives, method used, principal results and main conclusion. It must be concise and written in simple past tense.


Your abstract should be the last thing you write after the job is done.


Two Basic Types of Research


On this aspect, we are giving you simple explanations on the meaning of quantitative and qualitative research.


In the natural and the Social Sciences, quantitative research is based on the aspect of quantity or number. It’s used to investigate issues relating to objects that can be counted. It involves analysis of observable activities through the use of statistical, mathematical, and computational techniques. They are usually presented in percentages, mean, median, mode, etc.


Qualitative research on the other hand, is concerned with quality and variety. It involves looking closely at non-numerical data. It’s usually descriptive and harder to analyse than quantity data.


Research Population:


Research population is a large group of individuals or objects that is the main focus of a research or scientific investigation. It is for this purpose that the research is done.


It is also known as a well defined group of people or objects that has similar features or common binding characteristics. For example, if you are carrying out a research on government officials, then the entire government officials are the research population.


Look at the topics below:
1. Social and environmental determinants of malnutrition of under 5 children attending Nyanya General hospital.


2. Effects of Minimum wage increment on the purchasing power of teachers in the FCT.


3. Factors affecting the choice of Career amongst Secondary School students in Kaduna state.


I want to believe that we have already identified the research population of each of the topics above.


For topic 1, the population is under 5 children attending Nyanya General hospital.


For topic 2, it’s the teachers in the FCT while for topic 3, it’s Secondary School students in Kaduna State. Specifically, your source or sources of data in any research is the population.




As already discussed, population is a large group of people or objects from which a researcher is expected to gather his data. Because of the large size, it’s impossible to reach every member of the population leading to the need to select a certain number to represent the whole. This is called a sample and the process of achieving this is called sampling technique.


Population Sample: A sample is simply a subset of the population which arises from the inability of the researcher to reach all the population


Sampling Techniques: There are two broad types of sampling technique; non-probability Sampling and Probability Sampling.


Non-probability sampling: This is the act of deliberately selecting some persons or objects from a research population without given equal opportunity of being selected to others within the population. Another name for this is convenience sampling. This is usually one-sided, biased or subjective. It’s generally easy, quick and less expensive. Therefore, it’s good for preliminary studies, focus group or follow-up studies. Non-probability sampling is deliberate and purposive. For example, using one of  the topics above, “effect of Minimum wage increment on the purchasing power of teachers in the FCT,” a researcher may decide to select some teachers as his respondents because they are close to him. The researcher has simply used non-probability sampling technique.


Probability Sampling: Probability sampling is simply giving every member of the population an opportunity to be part of the research. This is usually achieved through several techniques.


Simple Random Sampling: In this method, each individual in the population has the opportunity of being part of the sample. This can be conducted in three ways: One of the methods is the lottery method. If the desired sample is 300 from a population of 2000 people or objects, this would be written on papers and a lottery is conducted. In lottery method, each of the population is assigned a unique number and the numbers are put in a container and thoroughly mixed. Then a blind-folded researcher selects a number from the container. Whichever number is selected becomes part of the sample population. This can be done with replacement or without replacement.


Simple Random Sampling With Replacement: If you have a population of 20 houses on a street and you want to select 2, using Sampling with replacement, all the numbers of each of the houses can be put in a bowl or a hat, then pick a number, write it down and return it to the container. The possibilities are that a number can be picked twice or two different combinations can be achieved:


1and 1
1and 2
5 and 7
8 and 20


The advantage of this method is that, with replacement, the two respondents are independent. In other words, one does not affect the outcome of the other.


Systematic Sampling: Systematic sampling technique is a statistical method involving the selection of an item, or sample units (would be respondents) from an arranged sampling frame. Sampling frame is a list of all the population unit from which the sample unit can be selected. for example, let’s assume you are to select a sample size of 5 students from a list of 20 students, the sum total of the students is the sampling frame.


The most common type of systematic sampling is the equal-probability method. This sampling is done by selecting an item from a list at random and then every kth item or element in the frame is selected, where K is the sampling interval. For example if you have a sampling frame of 20 houses and you want to use systematic sampling to get a sample size of 5 houses, the 20 houses would be arranged in a numerical order, then randomly select an element and use the interval generated from your formula to get the rest respondents.


The formula is K=N/n, where N is the population size and n is the sample size. Using our example above, k=20/5=4. This means that the 4th element would be the interval after randomly selecting the first item. Supposing the randomly selected number is 2, to get our sample size using the internal (4th), we would be having 2, 6,10,14 and 18.


I guess it’s clear? Have a blessed day!