| University | Singapore University of Social Science (SUSS) |
| Subject | ANL252: Python for Data Analytics |
Answer all questions in this section.
Question 1
This credit facility dataset to be analyzed comprises records of customers’
demographics, amount owed, repayment history/status etc.
The data dictionary of this dataset is depicted in Appendix 1.
List the categorical and numeric variables in this dataset.
Question 2
Conduct four (4) data pre-processing tasks for the analysis of the data, explaining results obtained.
Question 3
Articulate five (5) relevant insights of the data, with supporting visualization for each insight.
Question 4
Perform linear regression modelling to predict the variable, B1, explaining the approach taken, including any further data pre-processing.
Question 5
State the linear regression equation and explain key insights from the results obtained in Question 4.
Question 6
Organization of Code The submitted Jupyter notebook will be accessed based on the following:-
• Readability, Consistency and Efficiency
• Well-documented
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