Data Insight: Understanding the Role of Qualitative and Quantitative Data in Decision Making

This presentation provides insights into the role of qualitative and quantitative data in decision making, including statistical analysis, regression, and time series. It also discusses the impact of big data on decision making and various data collection strategies. The presentation concludes with a summary of the key takeaways.

CW2 STRUCTURE

MEMBER'S CONTRIBUTION
Group Member name an student ID Slides Developed (Number)

INTRODUCTION
• In CW1, complete information about Sainsbury has
described
• Market research is a process of determine the viability of a
new service/ product with a help of research conducted
directly through the potential customers.

Introduction
Marketing research
Market research is the process of determining the viability of a new service or product through
research conducted directly with potential customers. Market research allows a company to
discover the target market and get opinions and other feedback from consumers about their
interest in the product or service. ref
Stages in the marketing research process
2
34
5
1
2
34
5
6

Marketing
Research
Data Collect
Quantitative
Data
Tool
Questionnair
e
Customer
Satisfaction
Stakeholders
Satisfaction
Employee
Performance
Process Data
Qualitative
Data
Tool Interview
Structured Unstructured Semi
structured
Thematic
Analysis
Statistical
Analysis
Correlation
Progression
Time Series

T1 – QUANTITATIVE DATA
• It is an information that can be measured in a
numerical form. In this, different statistical analysis
is performed on the basis of real life scenario to
make decision.
• Simply, it can be stated that the information which
can be quantify then it is considered as a quantitative
data.

T1 – QUANTITATIVE DATA (CONT.)
Role of questionnaire in collecting quantitative data
• The questionnaire used for quantitative data is easier to analyse and it can be used by many
researchers as well.
• The method does not took require any additional cost and that is why, researcher used this method.
• Through questionnaire, researcher can determine the best outcome and make decision for the welfare
of a company.

T1 – QUANTITATIVE DATA
(CONT.)
Questionnaire:
1: Are you satisfied with the Sainsbury’s offering?
• Highly satisfied
• Satisfied
• Neutral
• Dissatisfied
• Highly dissatisfied
2. Do you agree that company’s sales increases by using advance technology?
• Yes
• No
• Occasionally

T2 – QUALITATIVE DATA
• It describe the qualities or characteristic of the data that can be
observed and recorded. Also, it describe the attributes or
properties which an object possess.
• With the help of this, researcher can determine the frequency of
traits so that effective outcome can be generated.
Qualitative
Data
Interview
Structure Unstructure
d
Semi
structured
Survey Observation Group
Discussions

Qualitative
Data
Interview
Structure Unstructure
d
Semi
structured
Survey Observation Group
Discussions
Thematic
Analysis
Qualitative
Data Codes Themes

T2 – QUALITATIVE DATA (CONT.)
How to analyse qualitative data
• In order to analyse qualitative data in effective manner, only thematic analysis has performed which in turn
assist to derive better outcome by using different themes and charts.
• Through this, it can be stated that researcher can analyse the views of selected respondents that helps to
generate a better outcome. Also, it can be stated that under key themes, scholar can provide a valid outcome
and generate the same into an effective manner.
Role of the interview in collecting qualitative data
• Interview is consider one of the most common method that is used to determine the conversation between a
researcher and interviewee.
• It also assist to explain as well as better understand the concept so that experience can be determine by
evaluating the respondent’s behavior.
• It is generally containing open ended questions which provided in-depth information so that marketers can
determine the results effectually.

T2 – QUALITATIVE DATA (CONT.)
Example of qualitative research:
• Q1: Are you satisfied with the advance technologies used by Sainsbury?
• Q2: Do you think that company’s operations effectively improve by using advance technology?
• Q3: What are the different technologies used by the company to enhance sales?
• Q4: Does Sainsbury looking to implement any new technique in near future?

T3: CORRELATION (STATISTICAL
ANALYSIS)
• Correlation analysis in a statistical analysis is used to measure the strength of a linear relationship
between two or more variable that assist to compute an association.
• Also it can be stated that with the help of correlation analysis, scholar can provide a deep insight
regard to the linear relationship between two variable
• Positive correlation: Such type of correlation is used to determine the whether the variable is
move in same direction or not. It mainly exist when one variable decreases and simultaneously
other also decreases and vice versa.
• Negative correlation: When adverse relationship identified within a variable then such type of
correlation exists. In a perfect negative correlation, value indicated from -1 to 0
• No correlation – When the value reflected zero then it reflected that there is no correlation
between the variable.

T3: EXAMPLES OF
CORRELATION ANALYSIS
The service
offered by the
company
Satisfied with
the services
The service offered by the
company
Pearson Correlation 1 -.016
Sig. (2-tailed) .742
N 402 402

T3: REGRESSION (STATISTICAL
ANALYSIS)
• Regression analysis is used to determine the strength and character on a relationship between one
variable so that effective outcome can be generated.
• It is mainly used by applying the software in which two variable need to be determine that help to
ascertain the results in order to predict the future happening between dependent and independent
variable.

T3: EXAMPLES OF REGRESSION
ANALYSIS
ANOVA
df SS MS F Significance F
Regression 1 16.6401 16.6401 11.26881 0.015288
Residual 6 8.859903 1.476651
Total 7 25.5

T4: TIME SERIES
• Time series analysis is a way through which individual can analyse a sequence of a data point that is
collected over an interval of a time. It is also help an organization in order to understand the
underlying causes of trend and pattern within a time. There are four types of time series analysis
which is as mention:
• Types of time series
• Trend
• Cyclical
• Seasonal
• Random

EXAMPLES OF TIME SERIES
ANALYSIS
Figure 1: Sainsbury, Profit analysis 2021.

T5: ISSUES OF CORRELATION
ANALYSIS
Advantages Disadvantages Limitation
Assist to determine the strength
and direction of a relationship
It does not prove the cause and
effect between variable.
It is one of the most time-
consuming method when the
variable are not determined.
It is a cost effective strategy Does not determine the statistical
pattern between the variable
It only uncover relationship
between variable.
Assist to determine causation
experimentally
It does not provide a conclusive
reason of it relationship
Does not application to identify the
relationship between more than 2
variables.

T5: ISSUES OF REGRESSION
ANALYSIS
Advantages Disadvantages Limitation
Assist to make decision for the
business currently and into a
future.
It does not provide accurate data
when the input data has error
Only consider linear regression
Can be generated results easily
without any efforts.
Does not care of non-linearity Value of R and least square
regression are not resistant to
outlier
Easy to implement and interpret
the results
Does not provide results on the
categorical variable
It does not comply with cause and
effect relationship

T5: ISSUES OF TIME SERIES
ANALYSIS
Advantages Disadvantages Limitation
Help to determine the results in
complex pattern from input
It has expensive computation cost There are hard stuff in analyzing
results through time series and this
decrease the chances of presenting
result
Provide accurate prediction
regarding future
Difficult in measuring the results Different models need to be used
in order to determine the results
effectually.
Assist to analyse the possible
change in near future and Real
estate is entirely based upon
this.
Problem to determine the accurate
correct model
While working with time series,
there is authentic and real
unification of the theory.

T5: IMPACT OF BIG DATA ON
DECISION MAKING
The Role of Big data on statistical analysis is wide and some of them are as mentioned below:
• With the help of big data, company is able to interpret the results through statistical analysis and that
is why, company is able to analyse the results in an effective manner that further assist to information
the decision accurately.
• Through Big data, company generate statistics from stored data and analyse the results about an
underlying dataset that is attempts to describe.
• By providing different graphs and tables, it will be easy to determine the results and make prediction
for the future hat assist to create a better decision for the welfare of a company.
• Along with this, the need for a digital transformation and innovation are considered some of the key
drivers that is used for investing in artificial intelligence. This in turn help to create a better outcome
in different industries and the focus on statistical analysis is also help to create a better outcome.

T6: DATA COLLECTION AND USE
FOR DECISION MAKING
Data collection strategies Effective use Informed decisions
Using survey questionnaires It is considered as a good method for a data collection
because it is having a large population and provide a
valid outcome in order to generate a better outcome.
With the help of effective survey method, business
collect honest feedback and opinions, from the people
in order to derive a better decision.
Using interviews The method of Interview is consider one of the most
effective strategy which in turn assist to determine the
views of people and respond the same.
With the help of interview, company can generate a
better outcome regarding the company’s loopholes
can be improved by putting efforts over it.
Using focus group sessions This is mainly used as a qualitative approach in order
to gain an in-depth understanding related to issues and
assist to create a better outcome
This in turn help to develop a strong understanding
and inform decision pertaining to present the findings
in an effective manner. This causes a positive results
for the company’s growth and impact.
Randomised experiments This type of data collection strategy assist to eliminate
the source of bias in order to treat the assignment.
The selected strategy will be beneficial for the
company in order to create a better outcome because
selecting sample randomly will be more beneficial for
the business in order to stay ahead in the competition.

CONCLUSION
• Through the above, it has been identified that modern data has provide a valid outcome for the
company in order to explore the better understanding and opportunity for the company.
• Both qualitative and quantitative data assist the business to understand the structure and provide
better view to the managers so that they make effective decision.
• Further, study also concluded that both regression and correlation analysis always determine the
relationship between the variable that help to improve the results and make decision accordingly.
• Time series analysis also assist to create a better outcome in order to understand the fluctuation in a
trend that help to make decision accordingly.

REFERENCE
• Huda, M. and et.al., 2018. Big data emerging technology: insights into innovative environment for
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pp.23-36.
• Law, P.M., Endert, A. and Stasko, J., 2020, October. Characterizing automated data insights. In 2020
IEEE Visualization Conference (VIS) (pp. 171-175). IEEE.
• Miller, K.E., Glein, C.R. and Waite, J.H., 2019. Contributions from accreted organics to Titan’s
atmosphere: new insights from cometary and chondritic data. The Astrophysical Journal. 871(1).
p.59.
• Newton, J.E., Nettle, R. and Pryce, J.E., 2020. Farming smarter with big data: Insights from the case
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