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Leadership and Women in Statistics

Langue : Anglais

Coordonnateurs : Golbeck Amanda L., Olkin Ingram, Gel Yulia R.

Couverture de l’ouvrage Leadership and Women in Statistics

Learn How to Infuse Leadership into Your Passion for Scientific Research

Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women?s issues, this book provides a clear vision for the future of women as leaders in scientific and technical fields. It also shows how emerging and current leaders of both genders in many disciplines can expand their leadership potentials.

Featuring contributions from leadership experts and statisticians at various career stages, this unique and insightful text:

  • Examines leadership within the roles of statistician and data scientist from international and diverse perspectives
  • Supplies a greater understanding of leadership within teams, research consulting, and project management
  • Encourages reflection on leadership behaviors, promoting both natural and organizational leadership
  • Identifies existing opportunities to foster creative outputs and develop strong leadership voices
  • Includes real-life stories about overcoming barriers to leadership

Leadership and Women in Statistics explains how to convert a passion for statistical science into visionary, ethical, and transformational leadership. Although the context focuses on statistics, the material applies to almost all fields of endeavor. This book is a valuable resource for those ready to consider leadership as an important element of their careers, and for those who are already leaders but want to deepen their perspectives on leadership. It makes an ideal text for group leadership training as well as for individual professional development.

Fundamentals of Leadership. Fresh Opportunities and New Challenges for the Statistics Discipline. Project Leadership. Leadership Competencies. Leadership Development Platforms. Individual Strategies. Institutional and Network Strategies.

Professional Practice & Development

Amanda L. Golbeck is professor of biostatistics and associate dean for academic affairs at the University of Arkansas for Medical Sciences. She served in a variety of leadership roles from department chair to vice president and academic dean at four academic institutions. She currently teaches courses in public health administration and management and public health leadership, and she is a member of the American Statistical Association president’s workgroup on developing training in statistical leadership. Dr. Golbeck is an elected fellow of the American Statistical Association, an elected member of the International Statistical Institute, a past president of the Caucus for Women in Statistics, and a country representative to the International Statistical Institute Committee on Women. She earned a BA from Grinnell College, followed by MA degrees in anthropology and statistics, and a Ph.D in biostatistics from the University of California at Berkeley. She also earned certificates in educational management at Harvard University’s Graduate School of Education, leadership at the American Association of State Colleges and Universities’ Millennium Leadership Initiative, negotiation at the John F. Kennedy School of Government, and women in leadership at the American Academy of Neurology. Grinnell College, the Kansas Board of Regents, and the American Statistical Association have presented awards to her in recognition of her leadership.

Ingram Olkin is professor emeritus in statistics and education at Stanford University. He received a doctorate from the University of North Carolina, and before moving to Stanford, was on the faculties of Michigan State University and the University of Minnesota. He has written a number of books, and has served on editorial boards for statistical, educational, and mathematical journals. He has served as chair of the Committee of Applied and Theoretical Statistics, chair of the Committee of Presidents of Statistical