Roles of Quantitative and Qualitative Research in Modern Business | Desklib

This report discusses the roles of quantitative and qualitative research in modern business, including the importance of relevant questionnaire design, discussion guide and use, and correlation, regression, and time series analysis. It also covers the limitations of these techniques and how to improve data collection for business decisions. The subject is MG413 Data Insights and the course name and college/university are not mentioned.

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Contents
 Roles of quantitative market research in business
 Importance of relevant questionnaire design
 Role of Qualitative research in Business
 Importance of discussion guide and use
 Correlation. Regression. And Time Series Analysis
 Limitations of Correlation, regression
 How to improve collecting Data (when the data is required to
make business decisions)

Introduction
The main objective of this report is to learn about the various
function of research methodologies in a modern business.
Assessment of various information analysis techniques such as
correlation, time series and regression take place and problems
regarding these techniques are also discussed.Data really powers everything that we do.” — JeffWeiner.

The role of quantitative research in modern
marketing research and data analysis
 Quantitative research
 There are 4 types of Quantitative research
 Role of quantitative research in modern marketing research and data
analysis:Errors using inadequate data are much less thanthose using no data at all.” — Charles Babbage

The role of quantitative research: Questionnaire design with
examples of good practice

The role of qualitative research in modern marketing research and
data analysis
 Qualitative research:
 There are 5 types of Qualitative research:
 Role of qualitative research in modern marketing research and data analysis:

The role of qualitative research. The Interview Discussion
guide: design & use (with examples)

Correlation & Regression:
How & why it is used - with examples
Correlation and regression techniques are used for examine the relationship between
qualitative variables.
Correlation: This technique is used to express relationship between variable with
the use of an equation which is provide by liner regression.
Uses: It is used to measure a possible relation between two continuous variables.
Correlation vary from -1 (Absolute negative correlation) through 0 (no correlation) to
+1 (absolute positive correlation).
Regression: It is used to measure the causes and effect in on variable will affect
another one.
Uses: It is used to measure the relation between independent variable and
dependent variable. Regression analysis can measure a wide variety of relations.“Big data isn’t about bits, it’s about talent.” —Douglas Merrill

Time series:
What it is & how it is used - with examples
A time series is a collection of statistical data
arranged in chronological order. The main objective
of time series is to understand and evaluate effect in
economic variables at different time period.
Uses: It is used to measure the fluctuation
in economic variables and it is also used to evaluate
current action such as pattern recognition, weather
forecast and disaster perditions .

Critique of issues surrounding the analysis techniques
These techniques plays important role in decision making for a firm.
While computing these techniques individual facing many problems.
These techniques only consider linear relationships. Causes and
effect in two variable are not implied by a strong correlation.

Critique of issues surrounding the analysis techniques
Time series help a business in future decision making by analysing past data. It is very difficult
process which does not give exact value of the possible future outcomes. It is only useful in short
term business decision making, it could lead to wrong predictions.

How data can be collected & used to make informed business
decisions.
The data can be collect by three ways such as by directly asking consumers, by indirectly tracking
consumers and by appending other sources of data by company. There is a proper strategy needed to
collect data. Companies short and summarise this data to make future forecast . This data helpful in
future decisions such as launch new product according to consumer needs and maximise profits.

Conclusion
Both the quantitative and qualitative information analysis have significant impact on
modern business studies. Information analysis techniques are plays important role in
summarising information and future decision making process of the company. These
techniques includes correlation, regression and time series. It is also concluded that
company adopt various ways to collect data and further use it for decision making.

List of References
 Bonakdari, H. and et.al., 2019. Integrated Markov chains and uncertainty
analysis techniques to more accurately forecast floods using satellite
signals. Journal of Hydrology. 572, pp.75-95.
 Chagas, B.N.R. and et.al., 2018, December. Current applications of machine
learning techniques in CRM: a literature review and practical implications.
In 2018 IEEE/WIC/ACM International Conference on Web Intelligence
(WI) (pp. 452-458). IEEE.
 Goel, S. and et.al., 2019, November. Comparative analysis of various
techniques for heart disease prediction. In 2019 4th International Conference
on Information Systems and Computer Networks (ISCON) (pp. 88-94). IEEE.
 Li, J. and et.al., 2018. Big data in tourism research: A literature
review. Tourism Management. 68. pp.301-323.

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