Statistics and data science degrees Overhyped or the real deal

Statistics and data science degrees Overhyped or the real dealStatistics and data science degrees Overhyped or the real dealData science is hot right now. The number of undergraduate degrees in statistics hastripledin the past decade, and as a statistics professor, I can tell you that it isnt because freshmen love statistics.Way back in 2009, economist Hal Varian of Google dubbed statistician the next sexy job. Since then, statistician, data scientist and actuary have topped various best jobs lists. Not to mention the enthusiastic press coverage of industry applicationsMachine learningBig dataAIDeep learningBut is it good advice? Im going to voice an unpopular opinion for the sake of starting a conversation. Stats is indeed useful, but not in the way that the popular media and all those online data science degree programs seem to suggest.Super-employeesWhile all the press tends to go to the sensationalist applications computers that watch cat videos, anyone? the data science boom reflects a broad increase in demand for data literacy, as a baseline requirement for modern jobs.The big data era doesnt just meanlarge amounts of data it also means increased ease and ability to collect data of all types, in all walks of life. Although thebig fivetech companies Google, Apple, Amazon, Facebook and Microsoft represent about 10 percent of the U.S. market cap and dominate the public imagination, they employ only one-half of one percent of all employees.Therefore, to be a true revolution, data science will need to infiltrate nontech industries. And it is. The U.S. has seen its impact onpolitical campaigns. I myself have consulted in themedical devices sector. A few years back,Walmart held a data analysis competitionas a recruiting tool. The need for people that can dig into the data and parse it is everywhere.In a speechat the National Academy of Sciences in 2015, Steven Freakonomics Levitt related his insights about the need for data-savvy workers, based on his exper ience as a sought-after consultant in fields ranging from the airline industry to fast food. He concluded that the next-generation super-employee is someone with a bit of business sense, a bit of computing know-how and a bit of statistics under his or her belt.Data is increasingly being called on to inform all our decisions. But this broad utility means that it isnt sexy. The sexy jobs working onself-driving carsorGo-playing computers are going torequire morethan an undergrad major in statistics or a week-long bootcamp on prediction usingPython. In fact, I was once told by an industry colleague that the term data scientist was coined to placate Ph.D. physicists who were tasked with runninglinear regressionsall day long.So, the way I see it, there will be egghead types off at the edge of the field, and there will some folks doing the necessary drudge work, and there will be a lot of people in between, looking carefully at the data and trying to glean useful insights. But and this i s the big point everyone had better know how to makebasic graphsand poke around adatabase.So where do I sign up?Five years ago there was no such thing as a data science degree, and nowthe listruns for pages and pages. And thats not counting the traditional statistics programs, or programs in related subjects like computer science or operations research. LinkedIns sidebar strongly feels I should consider an online masters degree in data analytics, from several different places.The proliferation of these programs speaks to the inadequacy of many peoples undergraduate educations in terms of statistics and data competency. Although stats majors have tripled, there were only 3,000 last year, compared to370,000 business degrees and 117,000 psych degrees. mora of these students should certainly give statistics (or one of the newer data science degrees) a hard look, given that a bachelors degree is borderlinecompulsorythese days.But I worry that the premise behind the appeal of these degre es especially at the masters level is the idea that the technology alone can solve problems. Nothing could be farther from the truth. Statistics is a tool for understanding data, but cannot by itself understand anything. Probably the biggest mistake people make when applying statistical or machine learning methods is not recognizing that the data being analyzed is insufficient to answer the relevant question. A degree that teaches you only about the hottest predictive analytics technology, likedeep learning, is a bit like learning how to drive without knowing the first thing about how to navigate.Setting realistic expectations for the added value of a statistics education is important to me because Im a true believer. I feel that more people should learn statistics and how to analyze data because it is a powerful way to understand modern life. In addition to boosting ones job prospects, a statistics education can teach you when toignore your doctors bad advice, help you understand important financial ideas and, in general, help you bewrong less often. ansicht real virtues are undermined by big data hype.So yes, lots more folks are studying statistics at the college level than in the past and, absolutely, even more people should be. But I think focusing on the surge in data science specialists is misinterpreting the nature of the demand. Everyone should have more of these skills, even if it isnt their primary job title.P. Richard Hahn, Associate Professor of Statistics, Arizona State UniversityThis article is republished fromThe Conversationunder a Creative Commons license. Read theoriginal article.