Comprehensive Analysis of Banking Data & Qualitative Interview Project

This project presents a comprehensive analysis of banking data and qualitative interviews. Part 1 focuses on analyzing banking data using SPSS, including data visualization techniques like histograms and pie charts, as well as identifying relationships between variables through scatter plots. Descriptive statistics are used to interpret the data. Part 2 delves into qualitative interview analysis, discussing both deductive and inductive approaches, including thematic and narrative methods. It covers interview techniques, data collection methods (including feedback), and the process of organizing and analyzing qualitative data. The project also includes a questionnaire with descriptive statistics and analysis of respondent answers regarding travel habits, preferences, and spending. The project combines quantitative and qualitative research methods to provide a holistic understanding of the subject matter.

Name of the University
Name of the Student

Contents
Part: 1:-..................................................................................................................................................3
Part: 2:-..................................................................................................................................................8
References:-.........................................................................................................................................25

Part: 1:-
Solution:-
Below is the data that we have created for the sake of our analysis. This data can
be looked as a banking data. The sample size is 20 and there are 8 attributes to deal with. The
purpose of any credit risk analyst is to minimize the days past due bracket of the particular
organization. The data that we are going to use here looks sound and significant to draw
statistical conclusions. We are using SPSS as a tool to extract statistical insights. Let’s look at
the data we have generated,
Sr.N
o Branch Age Sex
Liabilit
y
Income( in
INR) Bounce
1 Pimpri 40 M 2 10000 1
2 Hadapsar 45 F 3 12000 0
3 Nasik 46 M 4 15000 0
4
Thivanthapura
m 41 F 1 18000 0
5 Nasik 43 F 2 11000 0
6 Nasik 45 F 6 16000 0
7
Thivanthapura
m 47 F 8 18900 0
8 Pimpri 49 F 3 17200 0
9 Pimpri 51 F 2 16000 0
10 Pimpri 53 F 1 18790 0
11 Pimpri 55 F 3 19876 0
12 Pimpri 57 F 2 18763 0
13
Thivanthapura
m 59 F 3 15789 1
14 Hadapsar 61 M 2 7896 1
15 Hadapsar 58 M 3 9876 0
16 Hadapsar 59 M 3 14896 1
17 Hadapsar 60 M 8 18763 0
18 Hadapsar 61 M 12 20000 1
19 Hadapsar 62 M 5 28920 0
20 Hadapsar 63 M 6 8967 0
Loading the dataset in SPSS Directory,

SPSS has another window which is called Variable view, which opens side by side to
the Data view. It explains all the variable types and we shows if there are ant missing values.
Below screenshot does explain this,
We do plot this data graphically, which is the best way of Data Visualization. Below is
a histogram of age of the 20 customers.

Next we are going to see the distribution of the Monthly salary of the customers. For this
we are going with Pie-chat below.
Next, we try to find the linear relationship between two variables, say age and income for
instance (if there exists). The easiest way to identify this is to plot a scatter plot of this two
variables. Below screenshot shows the way to do so.

The result i.e. the scatterplot is shown below,
In the next segment we do measure some descriptive measures and interpretation, first we
look for frequency distribution of Branch and Bounce.

The cumulative distribution and relative distribution of all the Branches are shown here
and we have a good insight while looking at the data.

Part: 2:-
Solution:-
Introduction:-
In modern days studies, we often deal with much complex data in
our hands. Quantitative studies do an immense help in retrieving and extracting valuable
insights from the data. Relying on some of the refined methods, interview transcripts is the
most significant resource to analyse and extract information out of it. We know that,
interviews are very much important to gather reasonable and confidential information from
the household and individuals. Content of qualitative data enables the researchers to provide
an unbiased result. The process helps us to be focused on the particular objective of the task
in hand (Graham, C., Bond, S. S., Gerkovich, M. M., & Cook, M. R. (1980).).
Ways to Analyse Qualitative Interviews:-
Deductive and Inductive are the two approaches that are mainly
used for Qualitative Analysis. Narrative and Thematic content analysis are two of the
methods that comes under Inductive Analysis.
Content Analysis via Thematic Method:-
The initial of thematic approach is to eliminate the bias out of the
data first and enduring the overarching impression on the data. It does not work with a
framework that has been designed earlier, i.e. there is no thumb rule of the mechanism. The
primary objective of this mentioned approach is to search for a pattern that persists for a long
term in the data.
Content Analysis via Narrative Method :-
Narrative method deals with the sensitivity of the responses that
we have got from the respondents of the interview. It does deal with the crucial point and
valuable aspects of the responses and finds their relationship with the objective of the task
and makes it in a presentable format.
The Deductive Approach:-
In Deductive analysis, the framework is pre-defined and the
structure that we use is familiar and does not gets deviated from one problem to another. The
categories are made earlier by the conductor of the research and after this they will try to
regress the predictors with the target. Every steps that we do take, are positively correlated
with the goal of the research. Inductive approach will help us to look for little to little
insights, which we can extract from the data, on the other hand deductive analysis deals with
some selective points of the researcher’s choice.
Tips for conducting an Interview of Qualitative type:-

The quality of any research depends on the authenticity of the data,
Context Analysis poses no difference here. But in real world scenario, gathering absolute true
information from the respondents is so much difficult. And furthermore, some valuable
information could have been lost between the whole process (Sadura, A., Pater, J., Osoba, D.,
Levine, M., Palmer, M., & Bennett, K. (1992).).
The Feedback Method of Data Collection:-
There are lots of procedures to accumulate qualitative data. But which is
considered the best of the them is the art of physically recording the interviews so neat and
accurately. It helps us to avoid bias and loss of data. This approach is very simple and easy to
adapt. All we have to do is to take notes by hand, and that is it.
Sorting the Research Recordings in an Organized Way:-
The first step is to begin with that recording solution, which is easy to use.
Based on the approach of the interview we have to adapt either video or audio method.
Recording approach is among the very effective methods of data collection purpose, as it
gives the respondents the absolute freedom to be themselves and which is much needed here.
Some important steps of content analysis:-
1. Reading the transcripts carefully
2. Illustration of the transcripts
3. Good Understanding about the data
4. Data segmentation
5. Scrutinization and analysis of the segmented data
6. Conclusion regarding the result.
A Questionnaire and response for qualitative interview is shown below,
1. What is your age?
1. What is your age?

Mean 3.5
Standard Error 0.13487115
Median 3
Mode 4
Standard Deviation 1.3471
Sample Variance 1.79787
Kurtosis -1.151741688
Skewness -0.167888993
Range 5
Minimum 2
Maximum 7
Sum 210
Count 100
Largest(1) 6
Smallest(1) 1
Confidence Level(95.0%) 0.26912786

2. What are the places that were travelled by you since childhood?
2. What are the places that were travelled by you
since childhood?
Mean 2.77
Standard Error 0.167574979
Median 5
Mode 4
Standard Deviation 1.15789
Sample Variance 1.34587
Kurtosis -0.38898
Skewness 0.48897
Range 4
Minimum 1
Maximum 5
Sum 279
Count 100
Largest(1) 5
Smallest(1) 1
Confidence Level (95.0%) 0.2289
Descriptive Statistics
Looking at the data in hand, majority of respondents (33.7%) have roamed at least 6 – 8
times since their childhood. So, it may be estimated that majority of the respondents does
have good experience here and so, the data which we have collected is much relevant.

Only 11.9% respondents do have experience of travelling of just 1 – 2 times. Here in this
analysis, the responses are measured in the scale of 1 – 5 for the purpose of analysis, e. g.,
for 1 – 2 times of travelling were given the score 1, and people who have travelled (11 or
more) is scored 5.
Therefore, in this analysis, the mean value is 2.77, which signifies that the average
number of respondents has travelled 3 – 5 times since childhood.
3. What is your occupation?
3. What is your occupation?
Mean 2.55
Standard Error 0.143107645
Median 2
Mode 2
Standard Deviation 1.431076447
Sample Variance 2.047979798
Kurtosis -1.045433731
Skewness 0.562075869
Range 4
Minimum 1
Maximum 5
Sum 255
Count 100
Largest(1) 5
Smallest(1) 1