Assignment | research and Statistical Method

RESEARCH AND
STATISTICAL
METHOD
STUDENT ID:
[Pick the date]

Question 1
A key process in research is sampling which is used to obtain a sample which can be used as
a proxy for the population of interest and thereby can be used to study the same. In sampling,
the researcher needs to decide on the requisite sample size. The decision is not straight
forward as a trade off exists with regards to estimate accuracy and the underlying resources
that can be deployed for the sampling process. Typically, standard error and sample size
share a inverse relationship which implies that a larger sample would make it more likely that
the underlying sample selected represents the population of interest faithfully. The problem
with taking a bigger sample is that greater resources in terms of finances and manpower will
be required to enable the same. The resources and manpower available for research is often
limited and hence prudence must be exhibited by the researcher in utilising the same (Flick,
2015).
In order to outline the requisite sample size, it makes sense to consider two pivotal aspects.
One of these is the dispersion in the target population. If the target population is highly
dispersed, then it makes sense that the sample size should be large so that this variation is
adequately captured. As a result, minimum sample size would be contingent on the extent of
variation. Additionally, minimum sample size would also be dependent on the underlying
MOE (Margin of Error) which is a function of the accuracy that the researcher desires in the
result. Hence, higher accuracy would imply lower MOE and a larger minimum sample size.
The above understanding is captured in the following formula (Hair et. al., 2015).
In the above formula, the dispersion in the population is captured by the standard deviation
while MOE captures the accuracy. The alphabet “n” captures the minimum sample size.
With regards to the study comprising of sample from Belgian banks, the sample selected is
representation of the population and includes about 21% of the population. Even though 1 out
of 5 employees has been included in the sample for each of the banks but this is not large
considering that the population is not homogeneous. The satisfaction level of bank employees
would be affected by gender, age, department, employee level etc. Since there is no
separation classification of these key attributes before random selection, hence it is pivotal
that the sample selected must be larger in size. If a lower sample size than the current sample

is chosen, then it is quite possible that the sample would not be representative of the Belgian
banks population. Hence, taking into consideration the heterogeneous nature of bank
employees along with the sampling technique used, it makes sense to have a larger sample to
ensure representation. As a result, the given sample size used for the study is justified (Taylor
& Cihon, 2014).
Question 2
The relevant sampling technique that has been currently used for the study is simple random
sampling. The key feature of this sampling technique is that there is a random selection of
requisite sample size from the population without taking any criterion into consideration. The
result is that in this selection technique, all the elements included in the target population
have an equal probability of getting selected (Hillier,2016). In the context of the given study,
each employee of a given bank has an equal chance of being selected for the study without
any regards to demographics, position etc. The various positives and negatives associated
with this particular sampling technique are indicated as follows (Hastie, Tibshirani &
Friedman, 2014).
Advantages
1) The key benefit associated with this technique is that it is quite simple to use and does not
require any technical knowledge unlike other random sampling techniques which are
comparatively more complicated.
2) As this sampling technique is simple to implement, hence the likelihood of error would
become comparatively lesser which enhances reliability.
3) Owing to the simplicity involved in the implementation of this sampling method, the
extent of resources required in terms of money, time and manpower is quite low especially
when compared with other random sampling techniques. Additionally, for homogeneous
populations, this sampling technique usually delivers a representative sample.
Disadvantages
1) A key issue with the usage of this sampling technique is in cases where there are certain
significant attributes which are key characteristics of the underlying population. Since the
sample is randomly selected without any filter for these attributes, hence there is a strong