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Comprehensive Guide to Installing & Building R and RStudio (Windows, macOS & Ubuntu) In this complete tutorial, we walk you step-by-step through installing R and RStudio across Windows, macOS, and Linux (Ubuntu) while setting up a reproducible, professional-grade data science environment. You’ll learn how to: Install R and RStudio on different operating systems Understand RStudio’s four-pane interface for scripts, data, plots, and environments Use Rtools45 on Windows to compile packages and build R from source Configure R correctly on macOS and Ubuntu Manage packages and dependencies with renv for reproducible projects Upgrade R safely while migrating libraries without breaking workflows This guide is ideal for beginners setting up their first R environment and advanced users managing cross-platform, production-ready data science projects. In the final stage, we connect your R setup to real-world data science workflows, including: Data cleaning & preprocessing Exploratory Data Analysis (EDA) A/B testing & statistical inference Machine learning foundations Hands-on practice integrates R, Python, Excel, and industry tools, with an optional capstone project to showcase real-world impact. 🎯 Who this is for: Data & STEM students, analysts, researchers, and professionals seeking a clear, structured pathway into statistics and data science. 📌 What you gain: ✔ A reliable R & RStudio setup ✔ Reproducible project workflows ✔ Practical, career-ready analytical skills 🌐 Connect & Learn with SeovoSolutions 📺 YouTube: / @seovosolutions 💼 LinkedIn Community: / 15098032 📸 Instagram: / seovo.solutions 🎵 TikTok: / seovosolutions 🌍 Website: www.seovosolutions.com 📩 Email: info@seovosolutions.com 👉 Subscribe for more tech training, insights, and learning resources from SeovoSolutions. #data #dataanalysis #statisticalanalysis #statisticalmethods #statistics #rprogramming #analysis #datascience #education #dataanalysis #matheducation #stemeducation