Essay on Quantitative Research Methodology for Smart Operations

This essay provides a comprehensive overview of quantitative research methodology, focusing on its application in analyzing smart operations. It begins with an introduction to the methodology and its importance in research. The essay then presents a detailed literature review, exploring various articles and journals to analyze the quantitative approach. Key aspects discussed include data collection methods (surveys, questionnaires), data analysis techniques (mean, standard deviation), and the process of hypothesis testing. The essay highlights the advantages of quantitative research, such as its structured approach and the use of numerical data, while also addressing its limitations, including potential ethical issues. Recommendations are provided for effective implementation, emphasizing the importance of identifying variables and ensuring a controlled research environment. The essay concludes by summarizing the key findings and emphasizing the role of quantitative research in forming inferences and confirming hypotheses.

Running head: ESSAY ON RESEARCH METHODOLOGY
Essay on Research Methodology
Quantitative Research Methodology
Name of the Student:
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Name of the Student:
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Introduction
The development of the effective research has been largely impacted by the inclusion of
the operations and development of the smart operations (Clemence, Doise and Lorenzi-Cioldi
2014). The inclusion of the research methodology helps in improving the possibility of analyzing
the work required for the completion of the work and the development of the final outcomes
from the project. The quantitative research methodology would be helpful for collecting
information and analyzing the data for forming the inference (Serrador and Pinto 2015). The
following assignment would develop a literature review on the research methodology of
quantitative nature for analyzing the development of the smart work alignment. The report would
include the analysis of the various articles and journals for developing the effective analysis of
the works for the implication management. The quantitative research methodology would be
helpful for forming the analysis of the research articles and utilizing them for the formation of
the final documentation. The research methodology is helpful for seeking confirmation of the
hypothesis for a specific topic. Apart from this, whenever a data in form of statistical results and
data is available, the quantitative method would be executed.
Literature Review of Quantitative Research Methodology
According to Padmore, Stark, Turkevich and Champion (2017), the quantitative research
method deals with numbers and measurable entities for investigation of their relationship using
metric values. The quantitative research method would involve the study of the variables
included in the topic and it ends with approval or rejection of the hypothesis developed. The
testing of the hypothesis set is done with the help of the numerical parameters for identifying the
research work completion and the data collection variables (Muratovic et al. 2015). The
quantitative method would be formed with the inclusion of the factors for the development of the
smart innovation analysis. The objectives of the quantitative methodology would deploy
effective mathematical model for the defining of the hypotheses and theories. Sun, Roth and
Black (2014) stated that the focus of the methodology is on the empirical relations and
mathematical values for the listing of the innovation and development. The process of
quantitative research methodology starts with data collection based on the hypothesis set so that
ample amount of data is collected for analysis. The data collection can be either primary (self-
collected) or secondary (using authentic data resources). The primary data can be collected using

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surveys, questionnaire, and correlation research (Kuehlewein, Sadda and Sarraf 2015). After that
the process includes the data analysis using mean (normal distribution) or standard deviation
(correlation coefficients or ANOVA or t-test).
The analysis of the study by (Edden et al. 2014) results in pointing out the characteristics
of the quantitative research methodologies namely deductive in nature, testing process,
controlled setting, numerical data collection, and analysis of statistical inference. It is clear that
the quantitative analysis involves the analysis of the data and numbers. The data and numerical
can be either collected from surveys and questionnaire or can be used from any other research.
The information collection would include the analysis of the research based on any specific
variable (Ducret, Quardokus and Brun 2016). It involves the study of the variables included in
the topic and it ends with approval or rejection of the hypothesis developed. The testing of the
hypothesis set is done with the help of the numerical parameters for identifying the research
work completion and the data collection variables. According to Bauer, Cubizolles, Schmidt and
Nigg (2016), the focus of the methodology is on the empirical relations and mathematical values
for the listing of the innovation and development. Hence, it can be easily stated that the process
is deductive in nature using the numerical data collection with inference developed using the
analysis of statistical tools (mean and standard deviation). The testing of the data is done by
analysis of the information collected from the data collection in controlled setting and
environment (Wu, Burda, Salakhutdinov and Grosse 2016). The research study would be based
on the testing results of the test processes for developing the final inference.
According to the study by Corominas et al. (2014), the quantitative research methodology
finds its use in numerous research papers due to its deductive nature. The methodology results in
bringing some inference on a study using the comprehensive numerical data and statistical tool.
It is helpful for deducing the correct application of hypothesis by evaluating whether or not the
hypothesis is correct. The compilation of the information using the frequent analysis of the data
would enable the implication of the successive information development (Mackenzie et al.
2015). The research methodology is helpful for seeking confirmation of the hypothesis for a
specific topic. Apart from this, whenever a data in form of statistical results and data is available,
the quantitative method would be executed. According to Price et al. (2015), the highly structure
methods of the data analysis would be helpful for evaluation of the data gathered through tools

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and equipment. The quantitative research methodology would be helpful for forming the analysis
of the research articles and utilizing them for the formation of the final documentation. It allows
the answering of the questions that are closed ended in nature with quantifiable answers
(Nakajima and Telyukova 2017). The process also finds it use for the development of the results
in objective language. The testing of the hypothesis set is done with the help of the numerical
parameters for identifying the research work completion and the data collection variables.
Iqbal et al. (2015) have listed the advantages of using quantitative research as helpful for
specific research problem, use of clear and independent variable, high level of reliability, and
minimum self judgement. The quantitative research method deals with numbers and measurable
entities for investigation of their relationship using metric values involving the study of the
variables included in the topic and it ends with approval or rejection of the hypothesis developed.
The methodology would help in ensuring that a specific problem in dealt for the study (Yuan et
al. 2015). The analysis of the works would be successfully implied with the consideration of the
topic for analysis. The methodology would help in defining some specific research problems and
answering them using the data analysis. The research problems developed for the consideration
of the factors for the involvement of the independent variable. According to Arlehamn et al.
(2016), the identification of the dependent and independent variables are very crucial for the
analysis of the factors for the development. The use of the domain for the primary data analysis
would result in leaving no scope for the self judgement. All the analysis would be done using the
primary data. The use of the statistical tool would result in developing high reliability factor
(Schmidt et al. 2015). The error coefficient can be reduced using the statistical tools and hence,
the output would be correct and appropriate. This type of research yields the appropriate
outcomes based on the hypothesis and variables with the help of the information and data
collected. The analysis would also ensure that the implication of the works would be supported
by the utilization of the smart work listing and development.
On the other hand, Son et al. (2016) have brought about the points of disadvantages of
using the quantitative research methodology as limited outcomes, lack of controlled
environment, expensive, and time consuming. These are the major drawbacks of using the
quantitative research methodology for the analysis study. The development of the study of the
factors for the development of the specific work compilation would be dependent on the

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utilization of the smart work completion. The complete study of the topic using quantitative
research methodology would result in the implication of the variable analysis with the
continuation of the work completion (Tedford, DeLapp, Jacques and Anders 2015). The
variables would be identified as the mathematical works implied with the continuation of the
analysis of the topic from numeric aspect. The involvement of the variable analysis would be
developed for finding out the analysis of the variables and the utilization management. The
outcomes of the study is limited by the hypothesis set. It can show either the stated hypothesis is
true of the stated hypothesis is false. The research methodology faces the problem of lack of the
controlled environment. For example: the mindset of the people taking part in survey or
questionnaire can be compromised due to any issue. It would result in forming the major issues
of the analysis of the factors for the development.
Son et al. (2016), are convinced that the main drawback or disadvantage of quantitative
research methodology is the time complexity. The process of quantitative analysis would include
the data collection, data analysis, and summary of analysis. It is clear that the quantitative
analysis involves the analysis of the data and numbers. The data and numerical can be either
collected from surveys and questionnaire or can be used from any other research. The
information collection would include the analysis of the research based on any specific variable.
According to Price et al. (2015), it involves the study of the variables included in the topic and it
ends with approval or rejection of the hypothesis developed. The testing of the hypothesis set is
done with the help of the numerical parameters for identifying the research work completion and
the data collection variables. The analysis would also ensure that the implication of the works
would be supported by the utilization of the smart work listing and development. The process
also exhaust huge amount of money as it involves the consideration of the specific work
improvement. The listing of the expensive cost management had resulted in forming the major
implication of the work.
Corominas et al. (2014), have pointed out some of the ethical issues that result in forming
the issues in executing the quantitative analysis of the numerical data and the formation of the
effective work development. The analysis would be implied with the continuation of the
quantitative research methodology. The ethical issues in the development of the quantitative
research methodology would include the anonymity problems, sensitive topic, and infiltration of

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the personal information (Tedford, DeLapp, Jacques and Anders 2015). These are the major
ethical issues related with the quantitative research methodology. The alignment has resulted in
forming the successful compilation of the information collected from the analysis. However, due
to the issues like data misinterpretation and infiltration would result in forming the issues for the
resulting information loss. According to Clemence, Doise and Lorenzi-Cioldi (2014), the ethical
issue can result in forming the issues in getting the participants to fill the form honestly. The
management of the information has resulted in listing the cohesive formation of the work
complement. The sensitive topic is another factor that would result in raising issues in the
quantitative research methodology (Yuan et al. 2015). The implication of the factors for the
general development of the technology innovation would result in forming the issues for taking
part in listing appropriate work completion.
Recommendations
The process of quantitative analysis include the data collection, data analysis, and
summary of analysis. The data and numerical can be either collected from surveys and
questionnaire or can be used from any other research. However, some issues like limited
outcomes, lack of controlled environment, expensive, time consuming, anonymity problems,
sensitive topic, and infiltration of the personal information have made the process to be omitted
and excluded from many research process. Some recommendations have been given for carrying
out the quantitative research methodology effectively,
Identification of the variables: The most crucial factor for the analysis of the quantitative
research is identification of the variables to be used. The implication of the variable analysis
would be effectively implied with the continuation of the work completion. The variables would
be identified as the mathematical works implied with the continuation of the analysis of the topic
from numeric aspect. The involvement of the variable analysis would be developed for finding
out the analysis of the variables and the utilization management. The support and development of
the mathematical tools would be dependent on the variable selected for the analysis.
Selection of the statistical tool: The statistical tool selection is a major part for the
deployment of the work to be done and the utilization of the effective work factor analysis. The
selection of the statistical tool would be dependent on the alignment of the work aligned with the
contribution of the improved innovation and technology development. The statistical tool

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selection has been supported by the utilization of the work to be done and the innovation work
limited. The implication of the work analysis would be successful with the alignment
development for the continuation of the specific work completion management.
Cross examination of the inference: The inference developed from the statistical
analysis would be dependent on the utilization of the mathematical data and numerical. The
inference that came out from the analysis must be analyzed for any mistake. The evaluation of
the results would be helpful for taking care of the activities. The inference would be effectively
employed with the continuation of the specific work completion and development. The
implication of the cross examination would help in confirming the development of the work
implication.
Conclusions
It can be said from the inference of the study that the research methodology had helped in
improving the possibility of analyzing the work required and the development of the final
outcomes from the project. The above assignment had developed a detailed literature review on
the research methodology of quantitative nature for analyzing the development of the smart work
alignment. It is concluded that the quantitative research methodology is a research method that is
helpful for forming the analysis of the research articles and utilizing them for the formation of
the final documentation. The testing of the hypothesis set is done with the help of the numerical
parameters for identifying the research work completion and the data collection variables. The
analysis would also ensure that the implication of the works would be supported by the
utilization of the smart work listing and development. The quantitative research method had been
dealing with numbers and measurable entities for investigation of their relationship using metric
values. The quantitative research method had involved the study of the variables included in the
topic and it ends with approval or rejection of the hypothesis developed. The analysis had
included the comparison of the advantages and the disadvantages of using the quantitative
research methodology. Some recommendations like identification of the variables, election of the
statistical tool, and cross examination of the inference had been given for the improvement of the
research methodology.

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References
Arlehamn, C.S.L., McKinney, D.M., Carpenter, C., Paul, S., Rozot, V., Makgotlho, E., Gregg,
Y., Van Rooyen, M., Ernst, J.D., Hatherill, M. and Hanekom, W.A., 2016. A quantitative
analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M.
tuberculosis infected South Africans. PLoS pathogens, 12(7), p.e1005760.
Bauer, M., Cubizolles, F., Schmidt, A. and Nigg, E.A., 2016. Quantitative analysis of human
centrosome architecture by targeted proteomics and fluorescence imaging. The EMBO
journal, 35(19), pp.2152-2166.
Clemence, A., Doise, W. and Lorenzi-Cioldi, F., 2014. The quantitative analysis of social
representations. Routledge.
Corominas, J., van Westen, C., Frattini, P., Cascini, L., Malet, J.P., Fotopoulou, S., Catani, F.,
Van Den Eeckhaut, M., Mavrouli, O., Agliardi, F. and Pitilakis, K., 2014. Recommendations for
the quantitative analysis of landslide risk. Bulletin of engineering geology and the
environment, 73(2), pp.209-263.
Ducret, A., Quardokus, E.M. and Brun, Y.V., 2016. MicrobeJ, a tool for high throughput
bacterial cell detection and quantitative analysis. Nature microbiology, 1(7), p.16077.
Edden, R.A., Puts, N.A., Harris, A.D., Barker, P.B. and Evans, C.J., 2014. Gannet: A batch‐
processing tool for the quantitative analysis of gamma‐aminobutyric acid–edited MR
spectroscopy spectra. Journal of Magnetic Resonance Imaging, 40(6), pp.1445-1452.
Iqbal, Q., Bernstein, P., Zhu, Y., Rahamim, J., Cebe, P. and Staii, C., 2015. Quantitative analysis
of mechanical and electrostatic properties of poly (lactic) acid fibers and poly (lactic) acid—
carbon nanotube composites using atomic force microscopy. Nanotechnology, 26(10), p.105702.
Kuehlewein, L., Sadda, S.R. and Sarraf, D., 2015. OCT angiography and sequential quantitative
analysis of type 2 neovascularization after ranibizumab therapy. Eye, 29(7), p.932.
Mackenzie, I.R., Frick, P., Grässer, F.A., Gendron, T.F., Petrucelli, L., Cashman, N.R., Edbauer,
D., Kremmer, E., Prudlo, J., Troost, D. and Neumann, M., 2015. Quantitative analysis and
clinico-pathological correlations of different dipeptide repeat protein pathologies in C9ORF72
mutation carriers. Acta neuropathologica, 130(6), pp.845-861.

9ESSAY ON RESEARCH METHODOLOGY
Muratovic, A.Z., Hagström, T., Rosén, J., Granelli, K. and Hellenäs, K.E., 2015. Quantitative
analysis of Staphylococcal enterotoxins A and B in food matrices using ultra high-performance
liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Toxins, 7(9), pp.3637-3656.
Nakajima, M. and Telyukova, I.A., 2017. Reverse mortgage loans: A quantitative analysis. The
Journal of Finance, 72(2), pp.911-950.
Padmore, T., Stark, C., Turkevich, L.A. and Champion, J.A., 2017. Quantitative analysis of the
role of fiber length on phagocytosis and inflammatory response by alveolar
macrophages. Biochimica et Biophysica Acta (BBA)-General Subjects, 1861(2), pp.58-67.
Price, T., Wadewitz, P., Cheney, D., Seyfarth, R., Hammerschmidt, K. and Fischer, J., 2015.
Vervets revisited: A quantitative analysis of alarm call structure and context
specificity. Scientific reports, 5, p.13220.
Schmidt, M.E., Chiao, P., Klein, G., Matthews, D., Thurfjell, L., Cole, P.E., Margolin, R.,
Landau, S., Foster, N.L., Mason, N.S. and De Santi, S., 2015. The influence of biological and
technical factors on quantitative analysis of amyloid PET: points to consider and
recommendations for controlling variability in longitudinal data. Alzheimer's & Dementia, 11(9),
pp.1050-1068.
Serrador, P. and Pinto, J.K., 2015. Does Agile work?—A quantitative analysis of agile project
success. International Journal of Project Management, 33(5), pp.1040-1051.
Son, J.Y., Lee, H.Y., Kim, J.H., Han, J., Jeong, J.Y., Lee, K.S., Kwon, O.J. and Shim, Y.M.,
2016. Quantitative CT analysis of pulmonary ground-glass opacity nodules for distinguishing
invasive adenocarcinoma from non-invasive or minimally invasive adenocarcinoma: the added
value of using iodine mapping. European radiology, 26(1), pp.43-54.
Sun, D., Roth, S. and Black, M.J., 2014. A quantitative analysis of current practices in optical
flow estimation and the principles behind them. International Journal of Computer
Vision, 106(2), pp.115-137.
Tedford, C.E., DeLapp, S., Jacques, S. and Anders, J., 2015. Quantitative analysis of transcranial
and intraparenchymal light penetration in human cadaver brain tissue. Lasers in surgery and
medicine, 47(4), pp.312-322.

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Wu, Y., Burda, Y., Salakhutdinov, R. and Grosse, R., 2016. On the quantitative analysis of
decoder-based generative models. arXiv preprint arXiv:1611.04273.
Yuan, Y., Liu, B., Xie, P., Zhang, M.Q., Li, Y., Xie, Z. and Wang, X., 2015. Model-guided
quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a
synthetic gene circuit. Proceedings of the National Academy of Sciences, 112(10), pp.3158-3163.