This document serves as the introductory chapter for the Statistics for Data Science course at the graduate level. It focuses on the fundamental principles of Exploratory Data Analysis (EDA), shifting the focus from simple computation to critical statistical interpretation . Topics covered: Measures of Central Tendency Measures of Dispersion Measures of Shape: Skewness and Kurtosis Data Visualization for Descriptive Statistics Multivariate Descriptive Statistics Chapter Lab Activity: Exploring the mtcars Dataset

Análisis estadístico de los estados operativos de pozos petrolíferos en Brasil

This project performs exploratory data analysis (EDA) on an e-commerce dataset using R. It includes data cleaning, revenue analysis, customer behavior insights, product performance evaluation, time-based trend analysis, and regression modeling. Key insights include top-performing countries, high-value customers, sales trends over time, and the relationship between quantity and revenue. Visualizations and statistical techniques are used to support data-driven conclusions.

This report provides an exploratory data analysis of the HC Corpora dataset (Twitter, Blogs, and News).

Penerapan algoritma EM pada penentuan kemungkinan 2 buah koin yang dilempar

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