Business Analysis: Significance of Population and Sampling Techniques

This document provides insights into the significance of population in research and various sampling techniques. It also explains the main difference between primary and secondary data, along with their advantages and disadvantages.

Business Analysis

Table of Contents
QUESTION 1...................................................................................................................................1
a) Significance of population..................................................................................................1
b) Sampling techniques..........................................................................................................1
QUESTION 2...................................................................................................................................3
Explaining the main difference between primary and secondary data ..................................3
Explaining advantages and disadvantages of primary & secondary data ..............................5
QUESTION 3...................................................................................................................................7
a) Mean...................................................................................................................................7
b) Mode..................................................................................................................................8
c) Standard deviation..............................................................................................................8
Question 4........................................................................................................................................9
Explaining management information system contribution in decision making ....................9
REFERENCES..............................................................................................................................12
APPENDIX....................................................................................................................................13

QUESTION 1
a) Significance of population
The research population is a large collection of an individual or object whose focus is to
relate the scientific query. Through population, researcher is able to observe the behavior, trend
and pattern in such a way that helps to interact with the world and answer the defined question
as well (Agénor, 2020). Thus, it can be stated that population is a complete set of all elements
who shared a common characteristic defined by sampling criteria. For each defined task, scholar
choose population that helps to derive valid output. For example, in order to conduct a study
upon obesity and its impact over elder age group, investigator choose old age group as a
population because it will be beneficial to answer the research question.
Therefore, the researcher arise questions which can be answered by population in order
to generate the best answers. Further, this is usually more feasible when the population is small
and 3easily accessible by the researcher so that effective results can be drawn. With the help of
Cornucopian theory it has been analyzed that human ingenuity can resolve different
environmental or social issues. In the same way, by considering the scenario it has been
analyzed that to introducing a holiday scheme, colleagues can selected as a population in order
to generate the best results.
Overall, it can be stated that with the help of population most of the individual are
selected as a sample in order to draw a valid result. It is so because derive results on the basis of
population is not possible and this in turn helps to provide the best outcomes (Mukoka,
Chibhoyi and Machaka, 2020). Further, in the research terminology, population have a common
characteristic through which researcher is interested in order to derive positive outcomes so that
it will distinguish from other groups as well.
b) Sampling techniques
In research term., sample is referred to the group of people and items which are chosen
from large population for measurement so that investigator is able to generalize the findings
from research sample to population as a whole. In the context of present scenario, it has been
analyzed that colleagues can be selected from the population so that company may determine the
holiday pay is a better option for the company or not. There are range of sampling technique
used by the researcher on the basis of their aim and objectives, such as:
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Simple random sampling: This is one of the most common sampling techniques used by
the researcher. Under this method, each member from the population has an equal chance to be
participant. Generally, the method is used when researcher has prior information about target
population (Saptono and Mine, 2020). For example, in order to examine the impact of flexible
working environment within company's employee performance, simple random sampling
method can be chosen in which 30 employees out of particular department can be selected
randomly. This in turn reflected that each individual have an equal opportunity to being
participated within a study.
Systematic sampling: In this method, scholar select members from population for a
regular interval that might helps to meet the defined aim. Also, it eliminates the phenomenon of
clustered selection and a low probability of contaminating data that assist to provide valid
results. Moreover, through systematic sampling strategy, investigator easily chooses sample for
a specific tenure with a degree of control. For example, if local NGO is seeking to form a sample
of 500 volunteers from a population of 5000 people, the researcher can select every 10th person
in the population in order to derive the best results.
Stratified sampling: It is another method of sampling which can be partitioned into sub-
population. So, it can be stated that with the help of division of entire population into smaller
one win which strata can be formed (in which member shared attributes like income, education
attainment). With the help of this method, researcher is able to provide proper control over the
population and also ensure that all the participants are equally participated within a study (Nayak
and Singh, 2021). For example, in order to determine the alcohol consumption rat among people
of UK, stratified sampling technique can be used in which sample can be chosen from sub-
category of ages i.e. 18 to 25, 25 to 35, 35 to 45 so on.
Quota sampling: This methodology is fall under non-probability sampling method in
which researcher decide and create quotas so that market research samples assist to gather valid
information. Also, the sample can be generalized to entire population. For example, government
may place a quota that is limiting to neighboring nation in order to import more than 15 tons of
food grain (Stehman and Overton, 2020). On the other side, this sampling technique is highly
used because it saves research cost and also monitor number of types of an individual who took
participate in the survey. Thus, it is reflected that it is easy process to carry out that helps to
derive best results within a limited time frame.
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Snowball sampling: Under this technique, participants are asked to help researcher in
order to determine other potential subjects. This method helps to minimize the risk which would
be desirable choice. Therefore, it can be stated that this method is used when investigation is
hard-to-reach groups and that is why, they took help of participant to identify the objects. For
example, in order to study the level of customer satisfaction among member of any club, it will
be more difficult to collect the primary data sources, unless the members were limited (Snoball
sampling: definition method, advantages and disadvantages, 2021). As a result, a direct
conversation performed between managers and researcher to examine the research aim. Also, the
method is cost effective and easily determine the samples that helps to meet the defined aim.
Through the above it has been clearly identified that there are range of sampling
techniques and this can be used on the basis of purpose of research. Similarly, in the context of
selecting fellow to identify their views over holiday pay scheme, simple random sampling
method has been used. This is simple to use and very cost effective so that some fellow will be
randomly selected in order to examine their perceptions (Guest, Namey and Chen, 2020).
Moreover, another reason for choosing the selected sampling technique is such that it is free
from bias in which scholar is able to derive the better outcomes. That is why, among all, simple
random sampling method is chosen in order to extract a research sample from a large population.
QUESTION 2
Explaining the main difference between primary and secondary data
There are various situation in organization in which collecting data in order to formulate
decision becomes essential. Hilton is large multinational organization in hospitality industry that
made it to collect data from all type of sources. It includes primary and secondary which are two
forms that are completely distinct from each other. The analysis of the collected data either
through the primary or the secondary research shall help the company in identifying the various
facts and figures such that the process of decision-making shall simplify and accordingly it shall
generating the various competencies for the future growth prospects of the hotel business.
Primary data is type of information that has been collected and utilized for first time.
This is gathered from the scratch to fulfill particular purpose like Hilton can conduct survey
among its employee to gather information regarding prevailing policies or any other subject
matter (D’Allerto and Raggi, 2021). It is the data that has been obtained directly from the
targeted sampling so can be considered as primary research. The primary research provides fresh
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information that has not been altered and previously used. This is the information that is
gathered through investigation, surveys or interviews by the researcher in order to draw
inferences regarding the research problem. It generally consumes higher time and resources and
also requires specialized knowledge to gather the data that is not already existing. But
simultaneously this is more authentic and reliable for the researchers as it is free from bias and
is more oriented to the research aims and objectives of the company.
Secondary data refers to that information which has already been collected by
researchers previously for fulfilling particular goal and available for other scholars to meet their
objectives. This can be avail from sources like search engines, books, journals, articles,
authorized reports, etc. it is widely taken into consideration for meeting the purpose of
supporting conducted research with theories and models (Cave and von Stumm, 2021). This
helps in gaining validation of specific gathered data through reaching conclusion to provide
appropriate set of knowledge. It aids organization to save time and efforts as data is available
easily to attain certain predetermined goals. Such information is readily available to the scholars
so that the previous studies can be referred before drawing the conclusion and determining the
solution to the research problem. This cannot be considered much authentic and reliable data as
it shall be serving the aims and objectives that are previously framed and cannot be used without
the modifications as per the current study. It can also be affected by bias.
Primary Data Secondary Data
It refers to information which is to be collected
from the original sources by research himself.
This is type of data to be gathered by scholar
previously and utilized y another person for
another purpose than it has collected.
The methods for accomplishing primary data
comprises observation, survey, physical
testing, telephonic interview, case studies,
video diary entries, questionnaires, etc
From published sources like articles, local
bodies, state or central government, books,
magazines, journals, etc can be utilized to
collect the such type of information (Scott and
Kline, 2019).
Main reason for indulging into primary
research is to assemble information which can
attain specific objective and utilized directly
without making any manipulation (Gnann and
et.al., 2018).
These may be collected for multi purposes as
needed by the users to drive various kinds of
interferences from it after essential changes.
The authenticity of these sources collected
information is original as directly exerted by
scholar devoid of any kind of alteration
It is not original as assembled by users for own
purpose so there is chances of making
modification.
It is comparatively expensive as first time
collected.
Secondary data is already available from
several sources easily that made it less costly.
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Explaining advantages and disadvantages of primary & secondary data
There can be different advantages and disadvantages of the process of collection of data
in the business. As the coin has two sides there are pros and cons of each and every process. So
some major advantages and disadvantages of the two methods of data collection are:-
Primary Data (PD)
Advantages
 There are several benefits of taking PD into practice but one of the crucial aspect that
organization derives is its authenticity. This has been achieved for specific reason and
up to date data becomes available for having proper knowledge regarding specific
purpose.
 This is very accurate since attained from original sources to reach particular conclusion.
It becomes possible to address the targeted issue with help of PD. Company can give
appropriate interpretation via executing primary survey as it aids in connecting with
segment facing challenges, in addition to this, understanding and suggesting suitable
course of action to improve lacking areas can be exerted effectively (Bjärkefur, de
Andrade and Daniels, 2020).
 Proper control over sources and scale of information deriving through implementing this
mentioned course of practice. It provides several advantages through giving accurate,
reliable and original information.
 One of the most significant benefits are that it is in the hands of the researcher to define
the target population and accordingly the appropriate technique of sampling is applied so
that the reliable and valid conclusion for the research problem can be derived.
Disadvantages
 PD is expensive as require to get connected with targeted audience which is one of the
biggest cons of implementing primary research in organizational practices.
 Quality may decline if the process of assembling information is too lengthy and made it
out dated data as opinions, views, experience, etc changes on timely basis.
 Reluctance to participants in lengthy processing which can give false and unsuitable data
that may led top wrong decision making.
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 It needs the hiring of the skilled staff with much expertise so that they can perform the
research viably by taking the sample which involves all the major characteristics of the
population.
 It is a time consuming process which may also be affected by the availability of the
scarce resources in the organization in the form of time, money, manpower etc.
Secondary Data (SD)
Benefits
 It is most economical pattern that saves time and efforts & declines cost incurring in
order to obtain information.
 This play role of supporting primary data making more specific as provides information
regarding gaps, deficiencies, etc. SD gives assistance in attaining additional set of data to
fulfill purpose more effectively.
 Secondary data helps to improve understanding of problem through supporting with
theories, models, etc to validate research (Sangareddy and Aspevig, 2020).
 Basis for comparing data can be done effectively with help of SD in turn more
appropriate outcome scan be obtained.
 The major benefits are associated with the longitudinal analysis in which the company
shall be able to see the series of events that have occurred prior and accordingly shall be
able to analyze the current scenario and will be able to draw the inferences for the data of
the company.
 The data that is gathered from the secondary sources shall be helping the company derive
the deeper insights into the research problem and that is it generally preferred by the
researchers to conduct the study.
Drawbacks
 Secondary data may not be able to target with the research problems which provides
inappropriate outcome.
 Quality and accuracy of data may pose a problem in objective accomplishing purposes of
organization (Bahasoan and et.al., 2020).
 In this case many of the reliable sources are copyright protected and are not open to
access by the scholars. Apart from that they can be affected by the bias of the previous
researchers and this may provide the wrongful results.
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QUESTION 3
Data set
Sales revenue liquidity
2018 11597 3364 3640
2019 11747 10151 2436
2020 12317 10772 2127
a) Mean
Mean can be determined by adding all the numbers and then subtract the same by divide the
number of values within a data set. In order to calculate the values, following steps are used:
Step 1: calculate the values of each sub-section by adding all the values
Sales:
= 11597 + 11747 + 12317
= 35661
Revenue:
= 3364 + 10151 + 10772
= 24287
Liquidity:
= 3640 + 2436 + 2127
= 8203
Step 2: Apply the values within a formula = sum of all the number / total number of items
Step 3: Put the values derives in step 1 into step 2
Sales:
= 35661 / 3
= 11887
Revenue:
= 24287 / 3
= 8095.66
Liquidity:
= 8203 / 3
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= 2734.3
b) Mode
Mode refers to the repetitive number presented over a dataset or else can be stated that
values appears most often within a set of data. Here, there are no values consider as a mode
because of no repetition.
c) Standard deviation
SD = square root of sum of | x – mean|^2 / total number
Step 1 : determine the values of mean of each sub-section:
Sales = 11887
Revenue = 8095.66
Liquidity = 2734.33
Step 2: Find the square of the distance from its mean values
Sales
X (X – mean ) (x-mean) ^2
11597 11597 – 11887 = -290 84100
11747 11747 – 11887 = -140 19600
12317 12317 – 11887 = 430 184900
Revenue
X (X – mean ) (x-mean) ^2
3364 3364 – 8096 = -4732 22391824
10151 10151 – 8096 = 2055 4223025
10772 10772 – 8096 = 2676 7160976
Liquidity
X (X – mean ) (x-mean) ^2
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3640 3640 – 2734 = 906 820836
2436 2436 – 2734 = -298 88804
2127 2127 – 2734 = -607 368449
Step 3: Put all the values derived from step 2 into a formula
Sales
= square root of 84100 + 19600 + 184900 / 3
= Square root of 288600 / 3
= 310.16
Revenue
= square root of 22391824 + 4223025 + 7160976 / 3
= square root of 33775825 / 3
= 3355.38
Liquidity
= square root of 820836 + 88804 + 368449 / 3
= square root of 1278089 / 3
= 652.70
As per the appendix, it has been analysed that both values are same i.e. excel and manual
calculation. This in turn shows that the mean value of the all the variable of John Lewis for sales
is 11887. However, there is a need to enhance the revenue of a company by employing different
practices so that effective results will be generated.
Question 4
Explaining management information system contribution in decision making
Management Information System (MIS) is a systematic procedure that provides
assistance in taking effectual decisions. This refers to user machine interface system providing
data to support management, analysis, decision making, operations. It helps in achieving various
types of objective through enabling different segment to obtain relevant information for meeting
potential goals. MIS play important role in current era, there is high competition prevailing in
industry which requires an organization to be effective in order to derive reliable and updated
information. In addition to this, management information system provides assistance in adopting
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dynamic nature and serving relevant data with minimum time. For instance- Hilton is United
Kingdom based organization of hospitality industry that is one of the crucial sectors in
development of Nation. The current scenario of this sector is ever changing which forces
company to adopt capacity to cope up with this environment. Management Information System
play important role in giving regular information to top level managers to take decisions on the
basis of data rather than relying on predictions. This creates trend d patterns of decision making
on data taken into consideration which decides movement of organizational performance. It
takes into consideration technology, people, Hilton procedures to record, store and produce
information which can be used while making decisions.
Management Information System combines software, hardware and network products is
an integrated solution which provides guidance in decision making procedure. In addition to
this, MIS contribute largely in giving emphasis on all parts of functional areas through taking
people, components, etc of organization into practice (Role of Management Information System
in decision making, 2019). Manager of large organization requires having information regarding
market trend. It become possible when management ahs rapid access to data for formulating
crucial policies in respect to finance, operational, marketing, etc issues. In order to attain
objective of having access to information company collects data related to sales, customers,
financial records, inventory, manufacturing, etc. With help of such vast data reaching conclusion
becomes difficult for management of organization. MIS simplifies and speed up information via
network in turn taking decisions becomes quicker and accurate. Management information
system brings together data from outside and inside of company via setting up channel of
network among all its all hotel chain.
MIS comprises cognitive fit, dissonance, task technology, competitive strategy & socio
technical. Cognitive Fit Theory (CFT) can be taken into practice for understanding the MIS into
decision making procedure. It concentrates that the correspondence between information
presented format and task leads to higher performance. There is as well performance differences
that occur due to change in patterns of graphs, charts, etc utilized to reach outcome. In addition
to this, problem solver in organization seek to reduce challenges limiting information processors.
This is achieved by matching the problems representation of task which is known as cognitive fit
(Abu Amuna and et.al., 2017). From the evaluation it can be interpreted that company can
indulged into practices according to this model that views problem solving as the outcome of
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relationship between problem representation & task for analyzing type of information
emphasized. There are various purposes which validates that company should take the
management information system in its decision making process. In addition to this, it can be
interpreted that implementing MIS into business practices gives appropriate guidance in having
relevant , reliable and sufficient current data to formulate activities in order to achieve desirable
position. Hilton takes all these advantages through executing this specific procedure into its
business activities.
There are various factors that positively get impacted after implementing MIS into
organizational procedure. Hilton utilizes this method for making decision in respect to
formulating team or achieving specific targets. Having team collaboration becomes possible for
enterprise where there is essentiality of group, individual involvement. In sales department
having appropriate access on proper time is important which is attained by MIS as it permits to
derive information on all location (Huang, Huang and Chu, 2019). These aids in achieving
ability to work collaboratively to interpret results efficiently so that corrective outcome can be
achieved. It helps in finding lacking areas prevailing in entity and evaluates suitable course of
action to improve present scenarios. The potential effect of change on business process can be
identified by implementing MIS into company. For example-Sales department of Hilton can
make proper analysis regarding impact occur on customer hotel selection decision due to change
in its prices of services. MIS gives insights of reports regarding productivity, efficiency,
revenue, team sales, product performance, etc. it helps firms to compare actual performance with
estimated outcome to give information regarding lacking areas so that company can work on it
to improve. In addition to this, it has ability to change the direction of organization from failure
to success through emphasizing on crucial data set.
The management information system can be successfully implemented in the hospitality
industry to coordinate all the activities that are performed by the different departments and
integrate the efforts such that the organizational objectives can be achieved by the business. In
order to improve the guest satisfaction and to secure a long term benefit from them it is
important for the business to apply these systems such that proper lines of communication can
be build in the organization, and they are able to optimize the business processes and take the
efficient decisions to improve the overall financial health and growth prospects in the
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organization. It shall lead to the effective maintenance of the data and the processing of the same
such that the results can be applied to gain the operational efficiency.
12

REFERENCES
Books and Journals
Abu Amuna and et.al., 2017. The Role of Knowledge-Based Computerized Management
Information Systems in the Administrative Decision-Making Process.
Agénor, M., 2020. Future directions for incorporating intersectionality into quantitative
population health research. American journal of public health. 110(6). pp.803-806.
Bahasoan, A. N. and et.al., 2020. Effectiveness of online learning in pandemic COVID-
19. International journal of science, technology & management. 1(2). pp.100-106.
Bjärkefur, K., de Andrade, L. C. and Daniels, B., 2020. iefieldkit: Commands for primary data
collection and cleaning. The Stata Journal, 20(4), pp.892-915.
Cave, S. N. and von Stumm, S., 2021. Secondary data analysis of British population cohort
studies: A practical guide for education researchers. British Journal of Educational
Psychology. 91(2). pp.531-546.
D’Allerto, R. and Raggi, M., 2021. From collection to integration: Non-parametric Statistical
Matching between primary and secondary farm data. Statistical Journal of the IAOS,
(Preprint). pp.1-11.
Gnann, S and et.al., 2018. Improving copula-based spatial interpolation with secondary
data. Spatial statistics. 28. pp.105-127.
Guest, G., Namey, E. and Chen, M., 2020. A simple method to assess and report thematic
saturation in qualitative research. PLoS One. 15(5). p.e0232076.
Huang, J. C., Huang, H. C. and Chu, S. H., 2019. Research on image quality in decision
management system and information system framework. Journal of Visual
Communication and Image Representation. 63. p.102588.
Mukoka, S., Chibhoyi, D. and Machaka, T., 2020. Research Approaches and Sampling Methods
Paradox: The Beginning of Marginal Thinking in Research Methodology. Danubius
Working Papers. 2(1).
Nayak, J. K. and Singh, P., 2021. Fundamentals of Research Methodology Problems and
Prospects. SSDN Publishers & Distributors.
Sangareddy, S. R. P. and Aspevig, J., 2020. New Means of Data Collection and Accessibility.
In Public Health Informatics and Information Systems (pp. 289-305). Springer, Cham.
Saptono, R. and Mine, T., 2020, December. Time-based Sampling Methods for Detecting
Helpful Reviews. In 2020 IEEE/WIC/ACM International Joint Conference on Web
Intelligence and Intelligent Agent Technology (WI-IAT) (pp. 508-513). IEEE.
Scott, K. M. and Kline, M., 2019. Enabling confirmatory secondary data analysis by logging
data checkout. Advances in Methods and Practices in Psychological Science. 2(1). pp.45-
54.
Stehman, S. V. and Overton, W. S., 2020. Spatial sampling. In Practical handbook of spatial
statistics (pp. 31-63). CRC Press.
Online
Role of Management Information System in decision making. 2019. [Online]. Available through:
<https://yourbusiness.azcentral.com/role-management-information-systems-decision-
making-1826.html>
Snoball sampling: definition method, advantages and disadvantages. 2021. [Online]. Available
through: <https://www.questionpro.com/blog/snowball-sampling/>.
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APPENDIX
Sales revenue liquidity
2018 11597 3364 3640
2019 11747 10151 2436
2020 12317 10772 2127
mean 11887
8095.66666
66667
2734.33333
33333
mode #VALUE! #VALUE! #VALUE!
Standard
deviation 310.16 3355.38 652.7
14