MGT 555 Individual Assignment 1 Aina Najihah 4D PDF

Preview

Summary

FACULTY OF BUSINESS & MANAGEMENTLAB ASSIGNMENT 1MGT555: INTRODUCTION OF BUSINESS ANALYTICSNAME : AINA NAJIHAH BINTI ZAMZURIMATRIX NUMBER : 2019351101CLASS : BA2504DLECTURER : DR CHUAH SOO CHENGSUBMISSION DATE : 12TH APRIL 2020purpose are retraining, large appliance, other, repairs, education, us...

Description

FACULTY OF BUSINESS & MANAGEMENT

LAB ASSIGNMENT 1 MGT555: INTRODUCTION OF BUSINESS ANALYTICS

NAME

: AINA NAJIHAH BINTI ZAMZURI

MATRIX NUMBER

: 2019351101

CLASS

: BA2504D

LECTURER

: DR CHUAH SOO CHENG

SUBMISSION DATE

: 12TH APRIL 2020

Question 1

Question 2 a) Percentage of Loan Purpose 10.35% 5.41% 20.00% 0.94% 24.47% 1.41% 2.82% 0.47% 24.71% 9.41% 100.00%

Loan Purpose Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car Grand Total

Percentage of loans by different purpose 9.41%

10.35% 5.41%

24.71% 20.00%

0.47% 2.82% 1.41%

Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car

0.94%

24.47%

Report :

Based on the PivotTable and PivotChart, the highest percentage of taking loan because the purpose of small appliance. The lowest percentage of taking loan because the purpose of retraining. The highest percentage of loans taken by the purpose of small appliance is 24.71% and the lowest percentage of loans taken by the purpose of retraining is 0.47%. According to the ascending order of loan

purpose are retraining, large appliance, other, repairs, education, used car, business, furniture, new car and small appliance.

b) Count of Housing

Marital Status

Housing Type Other Own Rent Grand Total

Marrie d

Divorced 11 98 47 156

30 6 36

Singl e 41 164 28 233

Grand Total 52 292 81 425

Housing type according to Marital Status 180

Number of Housing Type

160 140 120 Divorced Married Single

100 80 60 40 20 0

Other

Own

Rent

Housing Type

This is a relationship between housing type and marital status. There are three types of housing which are other, own and rent. The marital status consists of divorced, married and single. Based on the PivotTable, housing type of “own’’ has the highest grand total for all marital status while the housing type of ‘’other” has the lowest grand total for all marital status. Also, from the table, the highest number of having house is single which is 233 out of 425 and the lowest number of having house is married person which is 36 out of 425.Based on the PivotTable, we can conclude that the highest number of housing type according to all marital status is “own” compared to “other” and ‘’rent”. Housing type own for single is 164, divorced is 98 and married is 30.

c)

This is a relationship between the number of loans by different purposes, marital status and credit risk. There are three PivotTables and three PivotCharts that can be derived.

Loan Purpose Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car Grand Total

Count of Loan Purpose 44 23 85 4 104 6 12 2 105 40 425

Number of loans by different purpose 120 100 80 60 Total 40 20 0 Bu

es sin

s Ed

at uc

n io

r e re Ca nc tu ni w lia r e p N Fu Ap ge r La

r he Ot

i pa Re

rs Re

tr a

n ini Sm

g

al

lA

lia pp

e nc U

d se

r Ca

Based on the PivotTable, the number of loans is 425. Loan purpose of small appliance has the highest number of loan taken which is 105 out of 425 and retraining has the lowest number of loan taken which is 2 out of 425. Count of Loan

Marital Status

Purpose Divorced

Married

Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car Grand Total

Single

Grand Total

14 13 44

4 1 5

26 9 36

44 23 85

1 37 2 6

1 8 1 1

2 59 4 5 1

4 104 6 12 2

13 2 36

60 31 233

105 40 425

32 7 156

Number of loan purpose taken by different marital status 70 60 50 40 Divorced Married Single

30 20 10 0 B

es in us

s Ed

at uc

io

n F

re i tu n ur r La

ge

ia pl Ap

e nc N

ew

r Ca

r he Ot

pa Re

irs tr Re

nin ai

g

Sm

l al

Ap

a pli

e nc Us

ed

r Ca

These data show the number of loans and marital status. There are three types of marital status which are divorced, married and single. Referring to the data above, the highest loan purpose that has been taken among marital status is single at amount of 233 out of 425 and the lowest loan purpose that has been taken among marital status is married person at amount of 36 out of 425. For the married marital status, the highest number of loan purpose is 13 which is small appliance and the lowest number of loan purpose is 0 which is other. For the single marital status, the highest number of loan purpose is 60 which is small appliance and the lowest number of loan purpose for single marital status which is retraining. For divorced

marital status, the highest number of loan purpose is 44 which is furniture and the lowest number of loan purpose for divorced marital status is 0 which is retraining.

Count of Loan Purpose

Credit Risk High

Low

Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car Grand Total

Grand Total

23 14 43

21 9 42

44 23 85

3 65 4 4 1

1 39 2 8 1

4 104 6 12 2

42 12 211

63 28 214

105 40 425

Credit risk on the loan purpose taken 70 60 50 40 High Low

30 20 10 0 B

s ine us

s E

t ca du

io

n F

ni ur

re tu rg La

e

ia pl Ap

e nc N

ew

r Ca

r he Ot

p Re

ai

rs Re

i tr a

n ni

g

Sm

al

l

ia pl Ap

e nc U

d se

r Ca

From all loan purpose and marital status, the grand total of low credit risk is higher than high credit risk which are 214 out of 425 compared to 211 out of 425. From above PivotChart, most of them have high credit risk on new car loan purpose which are 65 out of 211 and have low credit risk on small appliance loan purpose which are 63 out of 214.In conclusion, most of them took the loan for the purpose of new car and small appliance.

d) Count of Credit Risk

Gender

Credit Risk

F

High

78

Low

57

Grand Total

135

M 13 3 15 7 29 0

Grand Total 211 214 425

Credit risk according to gender 180 157

160 133

140 120

F M

100 80

78 57

60 40 20 0

High

Low

This is a relationship between gender and credit risk. Based on the PivotTable, the credit risk among both gender is relatively at low risk which is 214 compared to 211 which is high credit risk. Male has the highest taking loan which are 290 out of 425 while female has the lowest taking loan which are 135 out of 425. Based on the PivotChart, it shows that male is performed better at low credit risk than high credit risk while female is performed better at high credit risk than low credit risk.

e) Count of Loan Purpose Credit risk High Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car Low Business Education Furniture Large Appliance New Car Other Repairs Retraining Small Appliance Used Car Grand Total

Job Management 28 5 3 3 8 4

3 2 26 1 2 5 1

4 13 54

Skille d 135 13 9 31 2 40

Unemploye d 5 1

2

Unskille d 43 4 2 8 1 15

1 1 29 9 136 13 5 31 1 21

1

2

6 1 45 13 271

1

6

3 1 1

1 11

10 1 46 7 4 9 10 1 14 1 89

Grand Total 211 23 14 43 3 65 4 4 1 42 12 214 21 9 42 1 39 2 8 1 63 28 425

Credit risk according to different purposes and job

Management Skilled Unemployed Unskilled

0

5

10

15

20

25

30

35

40

45

50

This is a relationship between the number of loans by different purposes, job and credit risk. The type of job consists of unskilled, unemployed, skilled and management. As an overall information from the PivotTable, for all the loan purposes and all type of job have the low credit risk than high credit risk which are 214 out of 425 compared to 211 out of 425.Loan purpose of new car has the highest number of high credit risk while retraining and repairs purpose has the lowest number of high credit risk. Loan purpose of small appliance has the highest number of low credit risk while large appliance and retraining has the lowest number of low credit risk. It shows that skilled job person who took the loan for the new car purpose at highest number of high credit risk compared to all purposes at 40. Also, skilled job person who took the loan for the small appliance purpose at highest number of low credit risk compared to all purposes at 45. Thus, both high and low credit risk is the most applied by the skilled type of

job which are 271 in total. Unemployed person is the one who least applied for both high and low credit risk which are 11 in total.

Savings Data Statistics Summary Report

Savings Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Confidence Level(95.0%)

1812.562353 174.4939542 596 0 3597.28502 12940459.52 8.937463585 3.032593683 19811 0 19811 770339 425 342.9809012

Based on the Statistic Summary report of Saving data, the sum of all the values in saving data is $770339. The count of the data contained in saving data is 425. The mean or average of the savings is $1812.56. The median or the middle value in the data set is $596.Mode is the data value that occurs most often. The data set shows there is no mode. The standard deviation, 3597.2850 is the square root of variance. It measures the extent of the dispersion of the data from the mean. The variance 12940459.52 indicates that the data are widely spread out from the means. Kurtosis measures the degree of peakedness in the distribution curve whether peakedness of flatness of the distribution. The coefficient of kurtosis is 8.937 which indicates that the data is more concentrated around the mean since it is more than 3. Skewness measures the degree of skewness of a data set. The coefficient of skewness (CS) is 3.033 which shows that the CS is positive indicating right-skewed distribution and since |CS| > 1 indicates high degree of skewness. The maximum data is $19811.The minimum data is $0. The range, $19811 where its maximum data minus minimum data. It is rarely used as measurement because it does not indicate the actual distribution of data. The saving data was calculated by 95% of confidence level of interval.

Word count: 1540 words....