Statistical process control provides a mechanism for measuring, managing, and controlling processes. There are many different flavors of control charts, but if data are readily available, the X-Bar/R approach is often used. The following PDF describes X-Bar/R charts and shows you how to create them in R and interpret the results, and uses the fantastic qcc package that was developed by Luca Scrucca. Please let me know if you find it helpful!
5 responses to “Control Charts in R: A Guide to X-Bar/R Charts in the qcc Package”
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Thank you for this excellent getting started guide. Very clear, complete and easy to follow.
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Hi, i’am amazed of your guide, but can you please share the code in ui.R and server.R? i got problems in make it work
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This isn’t a Shiny app… just output from the qcc package.
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Hi Nicole! Your qcc explanation is terrific! Thanks so much! How are the dragons?
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More than amazing , thank you for your effort
Hello,
I’m Nicole
Since 2008, I’ve been sharing insights and expertise on Digital Transformation & Data Science for Performance Excellence here. As a CxO, I’ve helped orgs build empowered teams, robust programs, and elegant strategies bridging data, analytics, and artificial intelligence (AI)/machine learning (ML)… while building models in R and Python on the side. In 2025, I help leaders drive Quality-Driven Data & AI Strategies and navigate the complex market of data/AI vendors & professional services. Need help sifting through it all? Reach out to inquire – check out my new book that reveal the one thing EVERY organization has been neglecting – Data, Strategy, Culture & Power.
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