70 books like Mismeasuring Schools' Vital Signs

I was trained as a mathematician but have always been motivated by problem-solving challenges. Statistics and analytics combine mathematical models with statistical thinking. My career has always focused on this combination and, as a statistician, you can apply it in a wide range of domains. The advent of big data and machine learning algorithms has opened up new opportunities for applied statisticians. This perspective complements computer science views on how to address data science. The Real Work of Data Science, covers 18 areas (18 chapters) that need to be pushed forward in order to turning data into information, better decisions, and stronger organizations

I’ve been making web pages since the World Wide Web began in the mid-1990s. Back then, the web was visually quite sparse. It wasn’t until the late 2000s that new browser capabilities let the web get visually interesting and an exciting place for interactive graphics. Graphics are great: they can be informational (like charts and maps) or purely aesthetic. My personal journey of learning to code interactive graphics has been so rewarding that I’ve shared the love with others through teaching creative coding workshops and undergraduate courses. If you’re new to coding or computer graphics, I hope you’ll give one of these books a try!

As a child my heroes were designers and I thought designers could design across many disciplines, this was what I understood and aspired to. I'm fortunate to have been a designer, illustrator, and design teacher for many years. Passionate about the process I firmly believe if you can design in one area you can design in another. Understanding your material's potential is the key. As a tutor and author my job is to unwrap a student’s talent, support and encourage that unique view through skills building and advice to help them. I believe good design can solve many of the world’s problems and passing on that message is valuable.

I am an economist who came to realize that the marketplace of ideas was a political doctrine, and not an empirical description of how we came to know what we think we know. Science has never functioned in the same manner across centuries; it was only during my lifetime that it became recast as a subset of market reality. I have spent a fair amount of effort exploring how economics sought to attain the status of a science; but now the tables have turned. It is now scientists who are trained to become first and foremost market actors, finally elevating the political dominance of the economists.

I moved into content design from a career in brand and marketing, at a time when the discipline was emerging and not many people really knew what it was. Much of my time since has been spent educating people and organisations and sharing knowledge to help them make better content decisions. Throughout this time, I’ve learnt most of what I know through the experience of working with the design teams, but so many books have also helped me along the way and made my work so much better. I love content design – having the power to improve people's experiences with brands through words is so rewarding, and these books will inspire others to do the same.

As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!

I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.

I’m an Associate Professor in the University of Alabama’s Department of Philosophy. I worked as an FBI Special Agent before making the natural transition to academic philosophy. Being a professor was always a close second to Quantico, but that scene in Point Break in which Keanu Reeves and Patrick Swayze fight Anthony Kiedis on the beach made it seem like the FBI would be more fun than academia. In my current position as a professor at the University of Alabama, I teach in my department’s Jurisprudence Specialization. My primary research interests are at the intersection of philosophy of law, political philosophy, and criminal justice. I’ve written three books on policing.

It’s been fantastic to work in computer vision, especially when it is used to build biometric systems. I and my 80 odd PhD students have pioneered systems that recognise people by the way they walk, by their ears, and many other new things too. To build the systems, we needed computer vision techniques and architectures, both of which work with complex real-world imagery. That’s what computer vision gives you: a capability to ‘see’ using a computer. I think we can still go a lot further: to give blind people sight, to enable better invasive surgery, to autonomise more of our industrial society, and to give us capabilities we never knew we’d have.

I fell in love with technology when I wrote my first computer program at age 14 when there was no public Internet, no personal computers, no iPhone, no cloud. I have made technical contributions to every era of computing from mainframes, to PCs, Internet, Cloud, and now AI. I was recently elected to the National Academy of Engineering. AI currently surpasses my wildest imagination on the art of what’s possible. I'm still passionately working in technology at Google focused on how to live healthier lives. I believe we can make AI the telescope of the future, to helping everyone live long and healthy lives.