Determining Sample Size and Sampling Method in Research

RESEARCH AND STATISTICAL METHOD
STUDENT ID:
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Question 1
The researchers with regards to their research face an issue in relation to determination of
sample size which should be considered for the research. The key requirement of the
sampling process is for the selected sample to represent the population of interest in a faithful
and accurate manner. It is noteworthy that in relation of determining appropriate sampling
size, there is an inherent tradeoff involved which must be elaborated. In case of selection of a
large sample size, the chances of the sample being representative of the population tends to
increase but the downside is the additional costs involved in selection of this large sample
and the associated cost of data collection. On the other hand, with a lower sample size, it
may so happen that the accuracy is compromised owing to the sample not being
representative (Eriksson & Kovalainen, 2015).
Owing to the inherent trade off, it is essential to seek the determinants which enable the
researcher in deciding the requisite sample size that would be necessary. One of these is
obviously the accuracy which the researcher desires. In case of higher accuracy being
desired, a higher sample size would be more desirable as compared to a situation where the
accuracy requirements are low. Another factor is the heterogeneous nature of the population
which would tend to determine the appropriate sample size. The mathematical expression for
minimum sample size is also broadly based on these elements as highlighted below (Hair et.
al., 2015).
Thus, in line with the above formula, it is apparent that higher the heterogeneity in the
population of interest, higher would be the minimum sample requirement. Further, higher the
MOE or Margin of Error that is acceptable to the researcher, lower would be the sample size
requirement (Flick, 2015).
The current case needs analysis in the wake of above theoretical discussion. The population
of interest for the given study consists of 69,000 employees belonging to Belgian banks and
the selected sample size is 15,000 comprising about 21% of the population. The sample size
seems appropriate taking into consideration the heterogeneous nature of population as there
are employees from as much as 63 banks. Further, there are additional attributes which tend
to be divided these employees such as levels, gender along with educational status. Any

sample which is lower may lead to sampling errors and hence the chosen sample may not be
representative of the population, thus compromising the results of the study (Hillier, 2016). In
wake of the above discussion, it is fair that a large sample has been selected for the study
under consideration.
Question 2
The sampling method that has used to select the 21000 employees from the population of
63000 employees is simple random sampling. This is referred to a sampling method where all
the elements comprising the population have an equal chance of getting selected. For the
given research study, this may be carried out by labelling the employees with a unique
integer. Then using computer program, 21000 numbers can be randomly selected from the
pool of numbers allocated to employees. The employees corresponding to the numbers
selected would form the sample for the given research. The advantages and disadvantages
associated with the given sampling technique are highlighted below.
Advantages (simple random sampling)
1) The primary advantage of this sampling method is the convenience of use and limited
knowledge requirement. This is quite necessary especially when the sample size chosen is
significantly large (Flick, 2015).
2) Since in this sampling method, there is no need of any classification, hence any errors
which may be incurred on that count are absent in this sampling method (Hair et. al.,
2015).
3) It is an extensively used method which tends to result in representative sample selection
especially if the size of the sample is sufficiently large considering the population
characteristics (Eriksson & Kovalainen, 2015).
Disadvantages (simple random sampling)
1) The key issue with this sampling method is the biased sample which may be possible
when the sample needs to accurate represent certain key attributes. This aspect can be
substantiated with the example of the research study at hand. For the sample data, there are
a lot of critical attributes like gender, employee level, bank name which have to be fairly
represented. This tends to become difficult in case of random sampling since it can