Credit Card Fraud Analysis

Overview

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.

Data Loading

The dataset is loaded from ccf_simulation.csv.

Data Preprocessing

Data is preprocessed by converting relevant columns to factors and removing missing values.

Data Reduction

A subset of data is created, containing only specific transaction types (CASH_OUT and TRANSFER), and saved to ccf_red.csv.

Sample Selection

A sample dataset is created with 1000 fraud cases and 4000 non-fraud cases.

Summary Statistics

Summary statistics, including mean and standard deviation, are generated using the gtsummary package.

Data Visualization

A bar plot is created to visualize the distribution of transaction types by fraud status.

Hypothesis Testing

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.