This repository analyzes credit card fraud using a simulated dataset (ccf_simulation.csv). The analysis involves data preprocessing, exploratory data analysis, and hypothesis testing to determine if there is a dependency between transaction type and fraud status.
The dataset is loaded from ccf_simulation.csv.
Data is preprocessed by converting relevant columns to factors and removing missing values.
A subset of data is created, containing only specific transaction types (CASH_OUT and TRANSFER), and saved to ccf_red.csv.
A sample dataset is created with 1000 fraud cases and 4000 non-fraud cases.
Summary statistics, including mean and standard deviation, are generated using the gtsummary package.
A bar plot is created to visualize the distribution of transaction types by fraud status.
A chi-squared test is performed to test the independence of transaction type and fraud status.
Conclusion: There is strong evidence that the transaction type and fraud status are dependent.