QM162 Assignment Project on Introduction to Business Analytics
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Introduction
This project is interested in determining the level of poverty reduction through financial inclusion. The financial inclusion can always be realized when people are able to participate in the financial system and are able to start and invest in the education of their children. This study helps to disclose the extent to which the financial inclusion has been able to reach to the poor, women and the rural areas. To achieve this study was able to use secondary data that was collected from adults in the world and their characteristics and financial management of the people. The most important of this project is to inform that people on the use of financial services change over the years. This project will try to determine is the residence that owns a bank have a saving culture. The study also wishes to determine if the residence that owns a bank have a borrowing culture. And finally, the study is interested in determining if the person that owns a bank have borrowed in the past 12 months
The Hypothesis of The Project
- Null hypothesis: There is no relationship between bank account ownership and saving culture.
- Null hypothesis: There is no relationship between the bank account ownership and borrowing culture
- Null hypothesis: There is no relationship between the bank account ownership and borrowing behaviour in the last 12 months
To test this hypothesis, the project assumed that the dependent variables are binary and that there exists a linear relationship between the dependent and independent. The project will use the Phstat. The analysis will use the binary logistic regression since the dependent variables account holder is in category form.
Basic Information
From the variables collected in the Australia financial inclusion. The financial variables were categorical and hence the most appropriate statistical analysis was the logistic regression. The project, therefore, used the logistic regression. The descriptive statistic applied in this project is the frequency table since the variables are categorical
Descriptive analysis
| ACCOUNT HOLDER | Frequency | PERCENTAGE |
| Yes | 452 | 87 |
| No | 67 | 13 |
The table above gives the distribution of the account holder in Australia. The table indicates the 452 (87%) of the total participants were bank holder while 67 (13%) had no bank accounts. This means that there is a higher number of bank holder.
From the graph of those that borrowed in the last 12 months, it can be observed that there was the higher number of participants that did not borrow in the last one month than those that borrowed in the last one month.
The graph of those that borrowed
From the analysis, it can be observed that the proportion of those that had borrowing culture was higher than those that did not have the borrowing culture in Australia.
Data Analysis
The results below will evaluate the relationship between the account holders and the borrowing culture of the account holders. From the analysis, it can be observed that the p-value was 0.365 >0.05 significant level. This means that there was sufficient evidence to state that the borrowing culture among the account holders is not significant.
Deviance Table
Source DF Adj Dev Adj Mean Chi-Square P-Value
Regression 1 0.821 0.8208 0.82 0.365
borrowed 1 0.821 0.8208 0.82 0.365
Error 517 398.458 0.7707
Total 518 399.279
Model Summary
Deviance Deviance
R-Sq R-Sq(adj) AIC
0.21% 0.00% 402.46
Coefficients
Term Coef SE Coef VIF
Constant 1.386 0.559
borrowed
1 0.548 0.575 1.00
Odds Ratios for Categorical Predictors
Level A Level B Odds Ratio 95% CI
borrowed
1 0 1.7302 (0.5606, 5.3402)
Odds ratio for level A relative to level B
Regression Equation
P(1) = exp(Y’)/(1 + exp(Y’))
Y’ = 1.386 + 0.0 borrowed_0 + 0.548 borrowed_1
Goodness-of-Fit Tests
Test DF Chi-Square P-Value
Deviance 517 398.46 1.000
Pearson 517 519.00 0.467
Hosmer-Lemeshow 4294967295 0.00 *
From the logistic regression, it was observed that the logistic regression between the account holder and the borrowing culture. It was observed that the odds ratio for borrowing was 1.7302 with a confidence interval (0.5605, 5,3402) which contain a one. This means that there is not significant relationship between the borrowing culture and the account holder in the bank.
The relationship between the account holders and borrowing in the last 12 months
From the analysis, it can be observed that the coefficient of borrowing in the last 12 months had a p-value = 0.000 <0.05 significant level. This means that there was sufficient evidence that the borrowing within the last 12 months is significantly related to the account holding level among the people
Deviance Table
Source DF Adj Dev Adj Mean Chi-Square P-Value
Regression 1 17.56 17.5650 17.56 0.000
fin38 1 17.56 17.5650 17.56 0.000
Error 517 381.71 0.7383
Total 518 399.28
Model Summary
Deviance Deviance
R-Sq R-Sq(adj) AIC
4.40% 4.15% 385.71
Coefficients
Term Coef SE Coef VIF
Constant 2.359 0.188
fin38
1 -1.122 0.267 1.00
Odds Ratios for Categorical Predictors
Level A Level B Odds Ratio 95% CI
fin38
1 0 0.3255 (0.1930, 0.5491)
Odds ratio for level A relative to level B
Regression Equation
P(1) = exp(Y’)/(1 + exp(Y’))
Y’ = 2.359 + 0.0 fin38_0 – 1.122 fin38_1
Goodness-of-Fit Tests
Test DF Chi-Square P-Value
Deviance 517 381.71 1.000
Pearson 517 519.00 0.467
Hosmer-Lemeshow 0 0.00 *
From the analysis, it can be observed that the odds ratio for categorical predictors was 0.3255 (0.9130, 0.5491) which do not contain a one. This means that borrowing in the last 12 months has a significant relationship with the accounts holding.
Discussion and Conclusion
From the analysis, the project conclude that borrowing within the last one has a significant relationship with the account holding of the people within the country, the project also concluded that the borrowing culture of the people is not significant with the number of people who are account holders. Finally, the project of the study indicate that there was significant relationship between the saving culture of the people and the number of account holders