Topic 7
Methodology
Chapter 3. Research Design and Methodology
3.0 Introduction
What is this chapter about?
3.1 Research design
Which research is your research going to apply? Why is this design best
suited? Cite previous studies similar to yours that have applied the same.
3.4 Data collection procedures (or Data sources for secondary data)
3.5 Variable construction (if applicable)
3.6 Data analysis procedures
3.2 Target population
Population and sampling - Key terms
Population: all members of a specified group.
Example 1
Topic – Students in privates universities in Kenya
Population – All 600,000 students currently enrolled in all private universities
Example 2
Topic –Privates universities in Kenya
Population – All 65 private universities in Kenya
Note 1: Population must be measured in terms of your unit of analysis.
Note 2: You must provide an authoritative source of the number of objects
(subjects) in your population.
Target population: the population to which the researcher ideally wants to generalize.
Accessible population: the population to which the researcher has access.
3.3 Sample and sampling procedures
Sample: a sub-set of a population.
Sampling frame: refers to a list of the accessible population in which a researcher is able to
draw a sample.
, Subject (objects/participants): a specific individual participating in a study (sometimes
referred to as ‘case’).
Sampling technique: the specific method used to select a sample from a population.
What to consider in sample selection?
1- Representative (adequate) sample
2- Avoid bias in your sample selection. Selection bias occurs when the sample is selected
in a way that only a certain group or category of subjects are in the sample.
Example; Topic - Government financial assistance to SMEs
(a) Sample comprises of 50 SMEs involved in salon business.
Potential Bias – only salons are in the sample
(b) Sample comprises of 50 SMEs run by women
Potential bias – only female run SMEs are in the sample
3. Avoid bias in the sample selection. Self-selection bias occurs when the sample is
selected in a manner that certain categories of subjects will automatically be in the sample.
Example:
Topic – Financial experience of students in private universities
Accessible population (sampling frame) is 8,000 students in CUEA
Sample selection – I selected my sample of 50 students who attend mass at the Holy Trinity
Chapel on Sundays.
Potential bias – All the students in the sample are Catholics.
Sample selection – I selected my sample of 50 students from among those who were
cleared for exams during the Jan-Apr 2022 semester.
Potential bias – All these students are most likely the ones with a particular experience
(excludes all those who were not able to clear their fees)
(4) Random sample
Sampling
(a) Random sampling
Every case has the same probability (equal chance) of being selected. The best method of
sample selection.
(b) Stratified sampling
In stratified sampling, the population is divided into two or more groups called strata, and
random samples are taken in proportion to the population from each of the strata or sub-groups.
Examples of the latter include occupation, nationality, or possibly number of employees in an
Methodology
Chapter 3. Research Design and Methodology
3.0 Introduction
What is this chapter about?
3.1 Research design
Which research is your research going to apply? Why is this design best
suited? Cite previous studies similar to yours that have applied the same.
3.4 Data collection procedures (or Data sources for secondary data)
3.5 Variable construction (if applicable)
3.6 Data analysis procedures
3.2 Target population
Population and sampling - Key terms
Population: all members of a specified group.
Example 1
Topic – Students in privates universities in Kenya
Population – All 600,000 students currently enrolled in all private universities
Example 2
Topic –Privates universities in Kenya
Population – All 65 private universities in Kenya
Note 1: Population must be measured in terms of your unit of analysis.
Note 2: You must provide an authoritative source of the number of objects
(subjects) in your population.
Target population: the population to which the researcher ideally wants to generalize.
Accessible population: the population to which the researcher has access.
3.3 Sample and sampling procedures
Sample: a sub-set of a population.
Sampling frame: refers to a list of the accessible population in which a researcher is able to
draw a sample.
, Subject (objects/participants): a specific individual participating in a study (sometimes
referred to as ‘case’).
Sampling technique: the specific method used to select a sample from a population.
What to consider in sample selection?
1- Representative (adequate) sample
2- Avoid bias in your sample selection. Selection bias occurs when the sample is selected
in a way that only a certain group or category of subjects are in the sample.
Example; Topic - Government financial assistance to SMEs
(a) Sample comprises of 50 SMEs involved in salon business.
Potential Bias – only salons are in the sample
(b) Sample comprises of 50 SMEs run by women
Potential bias – only female run SMEs are in the sample
3. Avoid bias in the sample selection. Self-selection bias occurs when the sample is
selected in a manner that certain categories of subjects will automatically be in the sample.
Example:
Topic – Financial experience of students in private universities
Accessible population (sampling frame) is 8,000 students in CUEA
Sample selection – I selected my sample of 50 students who attend mass at the Holy Trinity
Chapel on Sundays.
Potential bias – All the students in the sample are Catholics.
Sample selection – I selected my sample of 50 students from among those who were
cleared for exams during the Jan-Apr 2022 semester.
Potential bias – All these students are most likely the ones with a particular experience
(excludes all those who were not able to clear their fees)
(4) Random sample
Sampling
(a) Random sampling
Every case has the same probability (equal chance) of being selected. The best method of
sample selection.
(b) Stratified sampling
In stratified sampling, the population is divided into two or more groups called strata, and
random samples are taken in proportion to the population from each of the strata or sub-groups.
Examples of the latter include occupation, nationality, or possibly number of employees in an
