Data-driven analysis on NYC taxi trips to explore how payment methods impact fare amounts, using descriptive analysis, hypothesis testing, and regression modeling to optimize driver revenue.

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A Statistical Analysis of Payment Behavior and Fare Pricing

Data-driven analysis of NYC Taxi trips to uncover how payment type influences fare revenue, using hypothesis testing and regression to guide driver revenue optimization strategies.

This project analyzes NYC taxi trip data to examine how payment methods impact fare amounts and driver revenue. Using data cleaning, exploratory analysis, hypothesis testing, and regression techniques, it identifies patterns showing higher fares for card payments and provides insights to optimize revenue strategies for taxi drivers.

This project analyzes NYC taxi trip data to explore how payment methods (card vs cash) influence fare amounts and driver revenue. Using statistical analysis and hypothesis testing, it identifies key trends in customer behavior and revenue patterns. The insights help recommend strategies to maximize driver earnings through optimized payment preferen

In this Project I Used Hypothesis testing To gain insights and Explore strategies to enhance taxi revenue through an in-depth analysis of payment methods. This repo dives into the correlation between payment types and fare pricing, offering valuable recommendations for optimizing earnings without compromising customer satisfaction.