Role of Research Methodologies in Business: A Detailed Project Report
VerifiedAdded on 2023/06/10
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This report provides a comprehensive overview of the role of research methodologies in modern business, focusing on both quantitative and qualitative approaches. It assesses various information analysis techniques, including correlation, time series, and regression, while also addressing the limitations associated with these methods. The report emphasizes the importance of data collection strategies and how companies can leverage collected data to make informed business decisions, such as launching new products and maximizing profits. It concludes that both quantitative and qualitative information analysis significantly impact modern business studies, aiding in summarizing information and guiding future decision-making processes.

Module Name
project Details
1: GROUP MEMBER: ID NUMBER
2: GROUP MEMBER: ID NUMBER
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project Details
1: GROUP MEMBER: ID NUMBER
2: GROUP MEMBER: ID NUMBER
3: GROUP MEMBER: ID NUMBER
4: GROUP MEMBER: ID NUMBER
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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)
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 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.
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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
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
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The role of quantitative research: Questionnaire design with
examples of good practice
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:
data analysis
Qualitative research:
There are 5 types of Qualitative research:
Role of qualitative research in modern marketing research and data analysis:
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The role of qualitative research. The Interview Discussion
guide: design & use (with examples)
guide: design & use (with examples)
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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
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 .
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 .
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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.
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.
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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.
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.
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.
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