UNIVARIATE ANALYSYS REPORT
Do yearly incomes, credit card expenditures, age and ratio of these expenditures to income vary significantly between customers with different card risk?
Yearly incomes
| Characteristic | no, N = 2961 | yes, N = 1,0231 |
|---|---|---|
| income | ||
| Â Â Â Â Mean (SD) | 30,685.1 (16,153.4) | 34,512.7 (17,071.2) |
| Â Â Â Â Median (IQR) | 25,900.0 (20,000.0, 36,250.0) | 30,000.0 (23,500.0, 40,000.0) |
| Â Â Â Â Range | 4,900.0, 110,000.0 | 2,100.0, 135,000.0 |
| 1 In $USD | ||
CONCLUSION:
We can observe that there people whose application for credit card has been accepted tend to have higher yearly incomes.
Age
| Characteristic | no, N = 295 | yes, N = 1,017 |
|---|---|---|
| age | ||
| Â Â Â Â Mean (SD) | 33 (10) | 33 (10) |
| Â Â Â Â Median (IQR) | 32 (26, 38) | 31 (25, 40) |
| Â Â Â Â Range | 19, 80 | 18, 84 |
CONCLUSION:
Age doesnât seem to have much impact on the outcome - the distribution for both groups of applicants is similar.
Categorical variables
Maybe thereâs something in categorical variables?
CONCLUSION:
People who are self-employed and donât own a home have significantly higher chance of being rejected.
CONCLUSION:
Obviously, having high number of derogatory mark indicates potential problem for the lender, therefore people with 5 or more derogatory marks got rejected.
Credit Card Expenditures & Share
CONCLUSION:
Expenditures of applicants who got rejected are equal to 0, therefore their ratio of monthly card expenditures to yearly income is also equal to 0.