Business Research Methodology

This document provides an overview of stratified random sampling, cluster sampling, convenience sampling, qualitative research, and quantitative research in business research methodology. It discusses the differences between stratified random sampling and cluster sampling, advantages and disadvantages of convenience sampling, and the distinctions between qualitative and quantitative research methods. The document also includes references for further reading.

Running head: Business Research Methodology 1
Business Research Methodology
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Business Research Methodology 2
Question 1
Stratified random sampling is an approach in which the population is divided into various
homogenous divisions referred to as ‘strata’, and the sample is randomly selected from each
stratum. Cluster sampling is an approach in which the population units are chosen in a
random manner from thro the already existing groups referred to as ‘cluster’ (Acharya,
Prakash, Saxena, & Nigam, 2013).
There is a random selection of individuals from all strata, in stratified random sampling, in
order to come up with the sample. Conversely, in cluster sampling, a sample is constituted
once all the individuals are selected from the chosen clusters and in a random manner.
Population units are chosen in aggregates in the case of cluster sampling, but in stratified
sampling, the elements of the population are singly chosen from each stratum.
Homogeneity exists between groups in cluster sampling, whereas homogeneity is present
within the group in the case of stratified sampling. In stratified sampling, heterogeneity exists
between groups, however, in the case of cluster sampling, the individuals in the group are
heterogeneous.
Sampling error can be minimized in stratified sampling by minimizing the differences within
groups among the strata while maximizing the differences between the groups among the
strata. On the other hand, the sampling error in cluster sampling can be minimized by
ensuring that the variations between the group are consistent with those in the population, and
the differences between the groups among the clusters are maximized (Singh & Masuku,
2014).
Question 2
Advantages of Convenience sampling

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Data availability
Convenience sampling has the primary advantage of being conveniently undertaken. The
study subjects are readily accessible within the researcher’s proximity, thus the researcher
does not have to strain to look for respondents to provide data.
Saves time
Convenience sampling method can be undertaken within a short time as compared to other
techniques. This is possible because the researcher is not with a requirement to carry out
comprehensive research for the whole population but to examine a representative sample that
is conveniently accessible.
Less costly
Convenience sampling is cost-effective because the researcher has a variety of options to
choose from and use the most appropriate one based on the availability of funds.
Significant for pilot studies
Convenience sampling is ideal for pilot studies because it helps to collect initial primary data
regarding the topic of study. Such outcomes can be used as indicators and assist the
researcher to decide on the next course of action. Based on the findings through convenience
sampling, one can gain insight into whether the research topic requires more insight or not.
Disadvantages of convenience sampling
A possibility of bias in data collection
The technique acquires data from a representative sample and not the whole of it. But in case
of over-representation or under-representation bias is likely to occur.
Incidences of sampling error

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Increased risk of bias due to selection leads will most likely result in inherent inaccuracies
known as sampling error.
Generalization of outcomes is impossible because of inherent bias which is most likely to
lead to misrepresentation of data (Farrokhi & Mahmoudi-Hamidabad, 2012).
Question three
Qualitative research is an inquiry method that provides insight into social sciences and on
humans, to ascertain the views and perceptions of individuals. Quantitative method is a
scientific and empirical approach that is utilised to produce statistical data, through the use of
statistical and mathematical approaches.
The quantitative research method is objective since the researcher is not intimately involved
and endeavours to specify the observations and topic analysis to answer the research
question. On the other hand, the qualitative method utilises a subjective approach because
the researcher is actively involved in the research.
The quantitative research method is significantly dependent on random sampling, in which an
extensive population is examined by selecting a representative sample from which the results
are generalized to the entire population. On the other hand, qualitative research method relies
on purposive sampling, in which a sample is chosen with an objective of obtaining exhaustive
insight into the target concept.
The objective of qualitative research is to explore and discover the concepts used in the
ongoing process. However, the aim of conducting quantitative research is to assess the cause
and effect association between study variables. In the qualitative research method, inductive
reasoning is usually applied to synthesise data, whereas deductive reasoning is applied in a
quantitative research approach.

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Data presentation in qualitative research commonly takes the form of words, images or
objects, while in quantitative research, data presentation will be in form of tables with
collected and analysed data in numerical form (Creswell & Creswell, 2017).

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References
Acharya, A. S., Prakash, A., Saxena, P., & Nigam, A. (2013). Sampling: Why and how of
it. Indian Journal of Medical Specialties, 4(2), 330-333.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and
mixed methods approaches. California, US: Sage publications.
Farrokhi, F., & Mahmoudi-Hamidabad, A. (2012). Rethinking Convenience Sampling:
Defining Quality Criteria. Theory & Practice in Language Studies, 2(4), 784-792.
Singh, A. S., & Masuku, M. B. (2014). Sampling techniques & determination of sample size
in applied statistics research: An overview. International Journal of Economics,
Commerce and Management, 2(11), 1-22.