Anexo de resultados estadisticos

Objective: To equip students with the skills to perform more sophisticated statistical tests within their Exploratory Data Analysis (EDA) workflow using the ggstatsplot package, create interactive visualizations, and publish RPubs using the Breast Cancer Wisconsin dataset.

US Avg. Effective Tariff Rate

trial

This exploratory data analysis (EDA) examines the Breast Cancer Wisconsin dataset to identify key cellular features—such as clump thickness, bare nuclei count, cell size, and cell shapes—that distinguish between malignant and benign cases of tumors. Using statistical tests and interactive visualizations, we assess their diagnostic potential and relationships. Findings confirm these features are strong predictors of malignancy.

This Exploratory Data Analysis (EDA) explores patterns in the Breast Cancer Wisconsin dataset. The goal is to understand how certain cellular features differ between benign and malignant tumors. Through visualizations and statistical tests, It highlight which features are most useful in identifying whether a tumor is likely to be benign or malignant.