Objective: analyze sample data set for statistical dependencies. 9 Variables were analyzed From the analysis above, the following were observed:
- The population is not ageing as a lot of the population is between 29 and 42.
- Only few persons pursued higher education degrees beyond the high school degree.
- Very few members of the population earned higher than the rest of the population.
- Job mobility is high as only few stay longer at a particular work place.
- Many people in the population are in debt.
- About 29% of the population defaulted on loans.
- Younger people had more defaults on loans. There are prevailing factors peculiar with the young: fashion, compulsive Disorder e.g. : shopaholics, little or no stable employment, loan seeking for education, misplaced or misguided priorities, and social factors.
- We also noticed that the number of people who defaulted on loans were more among those with a college degree (22 out of 30: 73%). Moreover, this was expected, as there is currently a rise in college loan debts among college students.
- People with larger incomes had lower debts (negative correlation between income and debt to income ratio).
- As debit to income ratio increased, there was a tendency for credit card debt to rise too.
- As income increased, there is a tendency for credit card debt to rise too. People with more money rend to spend more with credit cards, as the bank places a higher limit on the amount of money they can spend on their credit cards given the fact that their higher income is a guarantee they will pay back.
- As income increased, there is a decrease in the default on loans.
- As income increased, there is an increase in other debts. More income earners spend more and incur more debts.