Data Analysis using MATLAB for Credit Approval Data Set

Statistics
Matlab Assignment
Project Name – Introduction to Analytical Programming
Group Member –
Student ID –

Contents
Introduction........................................................................................................... 3
Background and Motivation................................................................................ 3
Data Analysis......................................................................................................... 3
Description and Summary of Data......................................................................3
Graphs................................................................................................................ 5
Analysis............................................................................................................ 10
Conclusion........................................................................................................... 12
References........................................................................................................... 13

Introduction
Background and Motivation
The aim of this project is to get an experience in data analysis using MATLAB. A file
available containing data can be analysed using MATLAB functions and commands. The
steps followed are:
1. The data files are downloaded and read into MATLAB using MATLAB commands.
2. The data is explored and analyzed and then a business application is formulated.
3. The missing values and the inconsistent data values are identified and handled.
4. The data is analyzed using statistical measures and graphs in order to find patterns,
trends, distributions or causality of data, forecasting, comparison etc.
5. The results are finally explained.
The data is available in a ‘data’ file. The ‘data’ file is imported to MATLAB and then
the data is filtered to remove any unnecessary rows. After this, the data is analysed by
using various types of graphs and calculations done using MATLAB commands. The
results obtained are then interpreted and conclusions drawn.
Data Analysis
Description and Summary of Data
The data set used is the Credit Approval Data Set [1]. We have complied with the policies of
using the data set ( It is taken form the site :
http://archive.ics.uci.edu/ml/datasets/Credit+Approval ). The data set is titled ‘ Credit
Approval ’. It is multivariate data and consists of various attributes. The source of this data is

confidential. The data is available as a ‘ data ’ file. It has been converted into a ‘ csv ’ file.
The file contains data related to credit card applications. There are some missing values also
in the data. There are 690 instances and 15 attributes ( A1 – A15 ) along with class attribute
( A16 ). 37 cases ( 5 % ) have 1 or more missing values (Missing values : A1 – 12, A2 – 12,
A4 – 6, A5 – 6, A6 – 9, A7 – 9, A14 - 13). The description of attributes is as follows:
A1: b, a.
A2: continuous.
A3: continuous.
A4: u , y , l , t .
A5: g , p , gg .
A6: c , d , cc , i , j , k , m , r , q , w , x , e , aa , ff .
A7: v , h , bb , j , n , z , dd , ff , o .
A8: continuous.
A9: t , f .
A10: t , f .
A11: continuous.
A12: t , f .
A13: g , p , s .
A14: continuous.
A15: continuous.
A16: + , - (class attribute).
The various attributes include the age , region , purchased item ( like PC , car , stereo , jewel ,
medinster , bike , furniture , amount of money on deposit in bank ( 10,000 yen ) , monthly
loan payment amount ( 10,000 yen ) , months expected to pay off the loan , number of years
working in the current company , etc. The attribute 16 (A 16) gives the sign positive and