- Information
- AI Chat
Research Methods - Lesson 6 - Methodology
Business Research Methods (DMS 502)
University of Nairobi
Related Studylists
vincentPreview text
1 | P a g e Ojalla George
STUDY AREA
The study area defines the limit of the study area or problem. To identify the study area, ask yourself.................... Where is this population to be found? The answer entails a description of the area in which research will take place. It includes:
- A map of the geographical coverage and area in hectares
- Climate in temperatures and rainfall
- Vegetation
- Transport structures
- Social, economic and demographic description. These are individual and household literacy, income levels, religion, marital status and occupation among others. The description should contain objective knowledge that other researchers have written about the area. ➢ Explain why the area was chosen in relevance to the research problem.
STUDY POPULATION
Population refers to all people who possess the characteristics of interest. It is a group of people or items from which you want to get information. This population must have specific boundaries and limitations which clearly indicates what to be included during your investigation.
For example if you were to conduct an investigation on health problem in location A. You must specify the boundaries of location A and people who live in this location in order for you to come with meaningful results. The study population here therefore, is everybody living within location A. Excludes:-
- Anybody else coming from neighbouring locations during the day of investigation.
- All visitors who happens to be in location A irrespective of where they come from during the day of investigation.
In many circumstances, you cannot use the entire population to do investigation. This is because of constraints of time and resources. Therefore, it is always recommended that, where you have such constraints, you should take a sample of the population.
SAMPLE SIZE DETERMINATION
The optimum sample size is directly related to the type of research you are undertaking. The rule of thumb should be to obtain as bog a sample as possible. However, resources and time tend to be major constraints in deciding on the sample size to use.
In social sciences, the following formula as designed by Fisher et al..,(1998) could be used.
2 | P a g e Ojalla George
Where:-
n= sample
Z= standard normal deviate (1) which corresponds to 95% confidence interval.
P= Proportion of target population estimated to have particular characteristics
Q= is the population without characteristics under investigation
q= 1-p
d = is the degree of accuracy (p-value = 0)
n = (1) 2 (0) (0) =
(0) 2
n = 384
When the population is less than 10,
Then nf= n
1+ (n/N)
Where
nf= is the desired sample size ( when the population is less than 10,000 )
4 | P a g e Ojalla George
sampling allows generalizability to a larger population with a margin error that is statistically determinable. Random sampling also allows the use of inferential statistics.
Some of the ways in which a probability sample may be drawn from a population:-
- Simple random sampling
A simple random sampling is obtained when each member of the target population is assigned a consecutive member and then selected randomly according to assigned number. To use this method, it is necessary to have a complete list of the target population. The researcher should decide on the sample size e. 50 students from a list of 500. The researcher can pick any number at random until he/she gets 50 students.
- Systematic random sampling
This technique consists of selecting every kth case in the population frame for inclusion in the sample. The following are the steps one would follow in selecting a sample using systematic random sampling:
- List all the first year students in the national university in random order e 00001 to 12000.
- Determine the sample size, e 500
- Determine the sampling interval by dividing the total population by sample size e 12000/500 = 24
- Blindly select from the table of random numbers the starting point. Because this number has to be between 0 and 10, you only have to consider the first or the last digit of the random number selected from the table. We should start from the student assigned the number 0 or 9 and the pick every 24th student.
- The process is continued until the required sample size is achieved. If the list of the
population is exhausted, start again at the top of the list, e the student assigned the number
- Multi – stage sampling
Typical example of multi stage sampling would be;-
- Determine the population
- Determine the sample size
- Randomly select a given number of provinces from the list of all provinces i. 4 out of 7
- Randomly select from within each chosen province schools from the list of all schools of the defined type. I. all public schools in the province.
- Randomly select from within each chosen school individuals from the list of all individuals of the defined type.
Advantages
5 | P a g e Ojalla George
- Saves time and energy
- Saves on cost
Disadvantage
- Sampling errors occur at each stage
- Stratified random Sampling
Stratification ensures that different groups of the population are represented in the sample. The population is divided into strata such as boys and girls schools, rural and urban schools etc. from which random sample are drawn.
To use stratified random sampling, one must first decide on the criteria under which the population and hence the sample will be stratified. For example, the criterion or variable used for stratification may be gender, income level, colour, size etc.
Stratified random sampling involves the following steps:-
- Identify the population
- Define the criterion for stratification
- List the population according to the defined strata or sub groups.
- Determine the required sample size and the appropriate representation in each stratum. This can be proportional or equal.
- Select using random numbers an appropriate number of subjects for each stratum.
The obvious advantage in stratified sampling is that it ensures inclusion, in the sample, of subgroup, which otherwise would be omitted entirely by other sampling methods because of their small numbers in the population.
- Cluster sampling
Cluster sampling is used when it is not possible to obtain a sampling frame because the population is scattered over a large geographical area.
In this method of sampling, groups and not individuals are selected. This occurs when it is either impossible or impractical to obtain a list of all members of an accessible population. In this method of sampling, it is assumed that clusters are similar in characteristics. Examples of clusters would include: - Schools, towns, city estates, hospitals, government ministries etc. The degree of generalization of research findings depends on the degree to which the clusters within the population are similar. Where the clusters are similar to a very high degree, cluster validity is said to exist. Cluster sampling involves the following steps:-
- Identify the population
7 | P a g e Ojalla George
to them will answer. Even among those, many will ignore the questions. Another example is where a researcher selects anyone who is convenient, such as a roommate or neighbor. The method is used in exploratory research where the objective is to gain insights rather than generalize results. The main feature of this method is that subjects are easily and conveniently available, and are also accessible. Researchers who use this method have little or no basis to argue that it is representative.
Purposive/judgment sampling
This is a deliberate nonrandom method of sampling which aims to select a sample of people/ settings or events with predetermined characteristic. A researcher who proposes to use purposive sampling more specify the criteria for choosing the particular cases e a certain age range, religious sect or educational level. A researcher who proposes to use purposive sampling must specify the criteria for choosing the particular cases.
Snowball sampling
This technique is used where no sampling frame exists and it cannot be created. The researcher begins by asking an initial group of respondents to recruit others they know are in the target group e. drug abusers. Anyone identified is contacted and asked if he/she would be willing to participate in the study and the cycle continues. The disadvantage of this method is that it includes only members of a specific group.
BIASES/ERRORS IN RESEARCH
During the process of sampling, there can be data errors/biases due to:-
✓ Variability of responses. Respondents can provide different answers to the same question. Fortunately this error is usually less than 5% making accuracy level 95%. ✓ Difference arising from the research instruments ✓ Differences because of interviewers’ knowledge, politics and culture ✓ The intention of the sponsor of research ✓ Design of instruments, for example ambiguity of questions ✓ Non responses ✓ Late returns of questionnaires ✓ Choice of unrepresentative respondents ✓ Processing of the questionnaires ✓ Interpretation of results
8 | P a g e Ojalla George
Research Methods - Lesson 6 - Methodology
Course: Business Research Methods (DMS 502)
University: University of Nairobi
- Discover more from:
