In this project, learners analyze a real-world sales dataset using R to understand business performance trends. The project involves data cleaning, handling missing values, and transforming raw sales data into a structured format. Students perform exploratory data analysis to identify top-performing products, seasonal trends, and regional sales variations. Using R visualization tools such as ggplot2, they create interactive and insightful charts and dashboards. The project helps learners understand how R can be used for business analytics and decision-making.

This project focuses on understanding customer behavior through data analysis. Learners work with customer demographic and transaction data to identify purchasing patterns. Using R functions and statistical techniques, they segment customers based on behavior, frequency, and spending patterns. The project includes data manipulation, clustering basics, and visual representation of customer groups. It builds strong analytical thinking and demonstrates how R supports marketing and customer analytics.

In this project, learners analyze a healthcare dataset to derive meaningful insights using statistical methods in R. The project covers descriptive statistics, hypothesis testing, and correlation analysis to study health indicators and outcomes. Learners interpret results and present findings through charts and summary reports. This project strengthens understanding of statistical concepts and shows how R is applied in research and healthcare analytics.