Of course, so is work in any of the sciences, so it is not surprising that many data-analytic methods are developed in the context of particular scientific fields and are then taken over by other disciplines. For example, the analysis of variance grew out of agricultural field trials and many time series techniques out of oceanography. Of course, probability and statistics are mathematical sciences, and so a taste and aptitude for mathematical thinking is a crucial ingredient. However, many students who have backgrounds in engineering, computing, physical and even biological sciences will have such aptitudes and interests, and we encourage them to conside applying.
Statistics is also, by definition, an information science.
So a background in computer science can also be a start for a statistician. Although this booket aims to give a general sense of what research in statistics is all about, it is also unashamedly focussed on activities at Stanford.