Who's afraid of statistics?

In recent years, there has been a real change in attitude towards statistics. Once considered a dull subject, it has experienced a renaissance, thanks in part to the ever-increasing amount of data organizations now collect.  

We spoke to Statistics Book Editor, Laura Briskman about the growing importance of data scientists in all fields of research and industry.  Laura is based in New York and is the driving force behind many of Springer Nature's statistics textbooks.

Statistics has become very popular recently, why has there been this shift in attitude?

I think that some of this comes from industry demand. The workplace—across many fields—is seeking statisticians and data scientists, which has motivated young professionals to seek training and education, which has, in turn, generated an increase in available courses, departments, and boot camps. As for the source of the industry demand: I think it comes from companies wanting to develop a more mature understanding of their own data.

Having knowledge of statistics has become important across a range of disciplines including HSS subjects – how can statistics help students and researchers in unrelated subjects?

We’re seeing statistics utilized to better understand politics and demography. Tools such as text mining are increasingly integrated into the humanities and social sciences; for example, you might see students programming in a literature course. We’re constantly reevaluating how statistics can play a role in arenas that are not innately quantitative.

I’d encourage everyone to take a look at our Quantitative Methods in the Humanities and Social Sciences series, which explores statistics and data science applications in film studies, literature, music, history, and more. There are some really interesting titles there!

Are there any new trends or emerging fields in statistics which we should be looking out for?

One delightful aspect of statistics is that it permeates other fields and conversations. What big conversations are we having right now, both in the US and globally? There’s a lot of ongoing concern surrounding the ethics of information sharing, and what responsibilities the private and public sectors hold in this space. Statistics will be invaluable in better understanding the nuances surrounding this issue. We’re also learning a lot about the spread of disease and related human behavior, as a result of the ongoing pandemic. Biostatisticians and epidemiologists are having some really interesting conversations right now. On a related note, our education system is undergoing a “forced pilot program,” of sorts, moving to online and hybrid platforms. How can statistics be leveraged to improve learners’, educators’, and administrators’ experiences?

Whether it is election outcomes or how long the pandemic will last, we look to statisticians to help us predict the future. What are the limitations of using stats to make predictions?

Speaking as someone who is not a statistician, I think it’s tempting to see statisticians as fortune-tellers. We’re in an age of frustrating levels of uncertainty, and I absolutely understand the compulsion to look to statisticians to help us make better sense of the world. But ultimately, statisticians are using imperfect data to build imperfect models, and those models predict possible outcomes, not definite ones. The statistics community can discuss how to improve these models and the research methods surrounding data collection, but it’s important to understand that statistics is not a realm of absolutes.

What makes the Mathematics & Statistics program at Springer Nature unique?

I love working for an international team. We have colleagues from the US, Hungary, Germany, Czech Republic, India, and Japan. We partner with an organization in India to produce our books, and we distribute them globally. Together, we represent authors from all over the world! As part of a company that prides itself on being a truly global publisher, I think this really keeps us innovative and forward-thinking; to flourish as a team and as a program, we must challenge our own cultural understandings on a continuous basis. And I think this is similarly necessary to properly advocate for our authors.

I also really appreciate the scale of the conversations that we have on this team: lots of conversations surrounding our ethical responsibility to the statistics community, how we can better support researchers and educators, especially in this very changeable time. And why not? The time is right for thinking big!

As an editor you acquire content for the statistics program, what kind of content are you looking for and how can authors submit a proposal?

Generally, I love to see proposals for new textbooks! If you’ve had trouble finding the right text for your own course, it’s entirely possible you’re not the only one. I also love seeing books on demography, and statistical explorations of cultural and ethical issues. If you have a book idea and you’d like to chat about it with me, to see if Springer Nature might be a good home for it, I’m always happy to discuss it. Contact me if you’d like a copy of our book proposal guidelines as well!

Editor Recommendation

Laura recommends the second edition of Springer Nature bestseller, An Introduction to Statistical Learning: with Applications in R, by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 

Expected for publication in Spring, its accessible treatment of statistical learning explores applications in data science for undergraduate students or nonexperts. The first edition of this book sold over 77,000 copies since its inaugural publication in 2013, and it boasts over 3 million chapter downloads. Indeed, it’s a true honor to have champion educators and groundbreaking statistical researchers James, Witten, Hastie, and Tibshirani with Springer Nature’s Mathematics & Statistics book program.

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