Testing district boundaries overlaying

TTD KM OS and PFS comparison for study 1 raw versus simulation

This report presents a comprehensive statistical analysis and data visualisation of a sales dataset using R programming. The analysis includes data preprocessing, descriptive statistics, correlation analysis, regression modelling, ANOVA, trend analysis, customer and regional analysis, and various graphical visualisations. The findings provide valuable insights into sales performance, profitability, customer behaviour, and business trends to support data-driven decision-making.

This project presents a comprehensive statistical analysis and exploratory data analysis (EDA) of the Chocolate Sales dataset using R. The analysis includes data cleaning, descriptive statistics, exploratory visualizations, correlation analysis, regression modeling, ANOVA, hypothesis testing, and time-based trend analysis. Various charts such as histograms, boxplots, bar charts, scatter plots, heatmaps, and line graphs are used to explore sales performance across countries, products, and salespersons. The project aims to identify key sales patterns, relationships between variables, and business insights that support data-driven decision-making.