Data Research & Management: Impact on Business Decision Making

This report provides an overview of qualitative and quantitative research methods, emphasizing their application in business decision-making. It explores the strengths and limitations of both approaches, highlighting the importance of in-depth understanding and statistical analysis. The report also discusses correlation, regression, and time series analysis as tools for interpreting data and identifying trends. It emphasizes how businesses can leverage these analytical techniques to inform strategic decisions by analyzing consumer behavior, market trends, and historical data. The conclusion underscores the necessity of combining qualitative and quantitative insights for reliable data-driven decision-making, referencing academic sources to support the analysis.

DATA
RESEARCH
&
MANAGEME
NT

QUALITATIVE RESEARCH
Qualitative research is used
for collecting, analyzing and
interpreting data by observing
what people do and say. It is
subjective. The nature of the
research is exploratory and
open minded, focuses on
personal in depth interviews
individually and focus groups.

• This mainly includes questions How, Why and What
• Process is very inductive
• Meaning can be constructed in a realistic way
socially
• In depth meaning can be attained
• Full of values
• Dependence on context is there
• Holistic approach is present
• Researcher is part of the process

STRENGTHS
• Its very detailed and in depth
• Not restricted to specific questions
• Guided by researcher
• Can be quickly revised
• Findings can be useful in more than one way

Limitations of Qualitative Research
• Dependent on
individual skills
• Difficult to maintain,
assess and
demonstrate
• Time consuming
• Difficult to
characterize in a
visual way

Quantitative Research
Quantitative Research aims to
measure the quantity and with its
comparison to the past tries to project
the future. This is more statistical
method. This gives the relation and
connection between empirical
observation and mathematical
expression of Quantitative
relationships. Used mainly to develop
mathematical models, theories or
hypothesis pertaining to phenomena.

Collecting numerical data for a particular outcome or variable to is
Quantitative Research
This is more logical data – statistics based data
This can be easily organized, analyzed and interpreted
It is impartial, unbiased and moreover neutral
Large sample size is present
• Analysis is carried out by the four (4) “W” (Who, What, Where and Why)

IMPORTANCE
Can be used in business to estimate attitudes of consumer and their
behaviors, marketing tactics.
In Medicine to measure clinical and methodological standards, trails
results many more
In economics to evaluate economic behavior and attitudes of citizens
and politicians

CORRELATION
Correlation is a statistical comparison tool which tells the extent to
which the given two variables move in relation to each other. And it
doesn’t show the reason for which the variables are changing.
REGRESSION
Regression is a statistical method that tries to valuate the
strength and character of the relationship between one
dependent variable and a series of other variables.

TIME SERIES
A time series is a set of data that
tracks the given sample and its
variance over a period of time. In
particular, a time series allows
one to see the influencing
factors from period to period.

Correlation & Regression
• Correlation just gives the values changed in relation with each other
not reveling the influence of each or any external factor on any one of
it
• Regression is the variable and the influences acted upon it for its
change but does not reveal the correlation with other variables
• By combining these two, we can get the necessary values of research
and give the exact determined value from a research

How to take business decisions
based on data research
• Whenever the data is collected by
any method either qualitatively or
quantitatively there will be large
data on our tables
• This will be further analyzed using
data analysis tools
• These are all numbers and pure
statistics