The non textbooks related to statistics & data science to recommend:

• The Lady Tasting Tea – How Statistics Revolutionized Science in the Twentieth Century, by David Salsburg, Henry Holt and Company, 2001
• The Theory That Would Never Die – How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy, by Sharon McGrayne, Yale University Press, 2012
• 《大数据 – 正在到来的数据革命，以及它如何改变政府、商业与我们的生活》，徐子沛，广西师范大学出版社，2013（豆瓣阅读提供来自理想国的电子版）
• Naked Statistics: Stripping the Dread from the Data, by Charles Wheelan,  W. W. Norton & Company, 2013
• AIQ: How People and Machines Are Smarter Together, by Nick Polson and James Scott, St. Martin’s Press, 2018
• The Language of Food: A Linguistic Reads the Menu by Dan Jurafsky, W. W. Norton & Company, 2014
• Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, by Cathy O’Neil, Crown, 2016
• Invisible Women: Data Bias in a World Designed for Men, by Caroline Criado Perez, Chatto & Windus, 2019
• Expecting Better: Why the Conventional Pregnancy Wisdom Is Wrong – and What You Really Need to Know, by Emily Oster, Penguin Books, 2014
• Science Fictions: The Epidemic of Fraud, Bias, Negligence and Hype in Science, by Stuart Richie, Bodley Head, 2020
• 当人工智能考上名校，[日] 新井纪子， 后浪丨民主与建设出版社，2020
• How Charts Lie: Getting Smarter about Visual Information, by Alberto Cairo, W. W. Norton & Company, 2020