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Ani AdhikariLecturer, Statistics |
Adhikari writes on a variety of topics, from stochastic processes to women in mathematics, and regularly teaches both Statistics 2, “Introduction to Statistics” and Statistics 21, “Introduction to Probability and Statistics.” She has been instrumental in developing Statistics 300, “Professional Preparation: Teaching of Probability and Statistics,” not only expanding the syllabus to provide valuable training for GSIs, but serving as a mentor and role model for them. A former student says, “Adhikari’s teaching methods are a tradition that should be passed down, which is why she came to mind when I was drafting my approach to teaching high school statistics for my honor’s thesis. To prepare, I attended her introductory statistics lecture to brush up on everything from the fundamentals to her style that still makes me nostalgic every time I think of her class.”
Statement of Teaching Philosophy
Statistics has become an indispensable analytical tool in many disciplines. My goal is to help my students to become discriminating users of quantitative information, whatever their field of work. In the process, I hope that they will all be stretched intellectually to reach a level beyond what they might initially have considered attainable.
Recently I have specialized in large introductory courses. These bring their own challenges, notably in the variety of students. To those who come in expecting the worst—and many do, convinced that the subject is a pack of lies—I try to show that statistics provides a sensible way of thinking about interesting questions, and that they are all capable of doing it well. I want all students to leave my class eager to use what they have learned. An introduction has little value, after all, unless it leads to something more. Indeed, I see it as my responsibility to draw promising students into the field, and I treat each class as an opportunity to attract future colleagues. I keep in touch with my students, long-distance if necessary, for years. The chats, the emails, the coffees, and the occasional prodding all make a difference. Students whom I taught as frisky undergraduates in their first statistics class become established professionals in the field. Their success tells me that I have done my job.
Teaching a big class requires meticulous organization, and technology helps. But my lectures are collaborations, not presentations. The students and I work together, and mathematics is a physically active process, like building—the hands must get dirty. Therefore I have made a conscious decision to keep the lectures mainly low-tech.
I owe a great debt to the GSIs, with whom I form a team—the class is ours rather than just mine. This sense of joint ownership brings out the best in all of us. I have been fortunate also to benefit from the wisdom of the many spectacular teachers among my colleagues, some of whom have fundamentally altered the way statistics is taught.
But in the end my greatest debt is to the students.Their intelligence, dedication, spirit, and good cheer are a constant delight. I hope that I show them just how important they are. Most of all, I hope that I can help them to look past the weekly routine, past the exams, past all the nitty gritty details, to see how much fun it is. For that is why we are all at Berkeley—to spend our days in inspiring company, doing what we love most.
Acceptance speech from 2006 Teaching Awards Ceremony