MG413 - Modern Marketing Research: Quantitative and Qualitative Roles

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This report investigates the roles of quantitative and qualitative research in modern marketing, examining how these methods are applied in data analysis. Quantitative research is crucial for understanding consumer behavior and formulating predictive studies using surveys and predefined criteria. Qualitative research enhances intelligence and trade functioning by identifying industry features. The report also defines correlation and regression as statistical methods for determining the degree of association between variables, while time series analysis uses sequential data to identify patterns and make predictions. Key issues regarding correlation and regression techniques, such as dependency, are discussed, along with the importance of effective data collection methods. The study concludes that both quantitative and qualitative research, along with data analysis techniques, significantly impact accounting and finance by aiding in data evaluation and predicting future corporate situations. Desklib provides access to similar reports and study materials for students.
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MG413 Data insights
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Table of contents
INTRODUCTION
Role of Quantitative research in modern marketing research and data analysis
Role of Qualitative research in modern marketing research and data analysis
What correlation and regression is and how it is used
What Time series is and how it is used
Issues regarding correlation and regression techniques
How data can be collected
CONCLUSION
REFERENCES
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Introduction
The purpose of this investigation is to understand about the role of
different investigation procedures in modern corporate inquiry, and
also how to apply different data analysis methods such as temporal
period analysis and correlations analysis.
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Role of Quantitative research
Qualitative statistics is used to investigate numerous company factors regarded to
be driving factors in shifting consumer behaviour. Basic analysis also helps with
the formulation of prediction studies for business estimates.
Many organisations utilise the polling method to do basic advertising research by
developing surveys for participants or potential clients. Survey design relates to
the procedure of producing or structuring a survey using established techniques in
a study aid.
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In modern advertising research, quantitative data is assessed under the supervision of a
thorough data gathering which is based on predefined criteria. These specific traits were
chosen by the advertising expert. Specific information analysis is possible because the
collection is created utilising an orderly arrangement of information and the graphing
concept under the supervision of the quantitative research method, enabling for specific
quantitative assessment.
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Role of Qualitative research in modern
marketing research
Improving intelligence and trade
functioning as a qualitative research allows
for the production of industry features
which are normally defined by both the
company and the researchers by extending
the survey's intelligence and data method.
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What correlation and regression
Correlation is a statistical method for
determining the degree of association
between 2 factors on a scale of -1.0 to
+1.0, with +1.0 representing positive
correlation and -1.0 representing negative
correlation. A zero correlation shows that
the 2 factors are unconnected.
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Time series
Time series statistics is a quantitative analysis method which analyses information
and statistics employing a sequence of data items collected over a set period of
moment. In time series analysis, researchers and experts collect data by keeping
stable patterns over period. Dickey Fuller's sales volume, for example, is predicted
into a time series evaluation all over those independent components such as seller
price, climate, customer needs, basic asset spendings, and shipment charges to find
out the amount of future sales for the next five years.
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Issues regarding correlation and
regression techniques
Dependency is important to consider because there is a lot of
interconnectedness in time series and correlation analysis. Moreover,
information from correlation and regression studies are often not
totally independent. As a reason, the results could be put to the test.
Whenever two things are not related at all in reality, correlation
analysis can produce significant positive or negative findings
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How data can be collected
In contrast to generating more informed choices, researchers must
ensure that the sources and techniques of data collection are effective
and acceptable for the research participant. In this case, big data can
benefit scholars in the knowledge obtaining process. Big data provides
far more effective answers to business difficulties and problems, and
also perspectives for management to take better selections.
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Conclusion
All quantitative and interpretive research have a significant effect on
modern accounting and finance, and data analysis methods such as
correlation, time series summary, and regression analysis aid the many
in evaluating data and accurately predict future corporate situations in
terms of preparation.
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REFERENCES
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region: A comprehensive exploration of the individual and contextual correlates of their uses. Travel
Behaviour and Society, 16, pp.77-87.
Dębniewska, M., Skorwider-Namiotko, J. and Wojtowicz, K., 2018. Risk assessment of tourism
companies listed on the stock exchange based on their financial reporting. Ekonomia i Środowisko.
Dietrich, C.F., 2017. Uncertainty, Calibration and Probability: The Adam Hilger Series on Measurement
Science and Technology: The Statistics of Scientific and Industrial Measurement. Routledge.
Kemsley, E.K., Defernez, M. and Marini, F., 2019. Multivariate statistics: Considerations and
confidences in food authenticity problems. Food Control. 105. pp.102-112.
Sall, J., Stephens, M.L., Lehman, A. and Loring, S., 2017. JMP start statistics: a guide to statistics and
data analysis using JMP. Sas Institute.
Stephens, M.A., 2017. Tests based on EDF statistics. In Goodness-of-fit Techniques (pp. 97-194).
Routledge.
Vargas-Solar, G., Zechinelli-Martini, J.L. and Espinosa-Oviedo, J.A., 2020, August. Enacting data
science pipelines for exploring graphs: from libraries to studios. In ADBIS, TPDL and EDA 2020
Common Workshops and Doctoral Consortium (pp. 271-280). Springer, Cham.
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