This repository contains four different hypothesis testing projects, analyzing real-world data to validate assumptions and drive data-driven decisions. Each project applies statistical tests (e.g., t-tests, chi-square, ANOVA) to uncover insights and support business strategies. Built with Python, Pandas, SciPy, and Statsmodels. 🚀

Use descriptive statistics to describe qualities of a sample, set up a hypothesis test, make inferences from a sample, and draw conclusions based on the results.

This project analyzes online advertising performance using Exploratory Data Analysis, Hypothesis Testing, and Regression Analysis. It examines key metrics like click-through rates, conversion rates, and ad costs to uncover insights for optimizing ad spend and improving campaign efficiency. Built with Python, Pandas, Scikit-Learn, and Statsmodels.