Project Summary: Factors Affecting Superstore Sales

Objective: The project aims to analyze factors influencing sales in a Superstore, utilizing a dataset sourced from Kaggle. The primary goal is to identify weak points contributing to lower sales, with a focus on specific goods in different regions. The ultimate objective is to provide insights that can assist the Superstore in optimizing its strategies and increasing overall sales.

Data Source: The dataset, comprising 13 variables, originates from Kaggle Datasets and represents the sales data of a Superstore. The dataset includes information on shipment modes, quantities, cities, states, categories, and other relevant factors. With 9994 observations, the dataset is comprehensive, containing no missing values.

Key Issues/Problems to Address:

Identify factors contributing to lower sales. Explore regional variations in sales for specific goods. Provide actionable insights to enhance sales performance. R Packages for Analysis:

Hmisc - Data analysis and character string manipulation. psych - Basic descriptive statistics. rlang - Evaluation of variables and functions. RColorBrewer - Color schemes for plotting graphs. tidyverse - Data transformations. maps - Geographical uses. GGally - Combining geometric objects with transformed data. Forecast - For forecasting purposes.

Background Information: The dataset itself is expected to provide sufficient information for analysis. External background information may not be necessary due to the comprehensive nature of the dataset.