The ASCCR Frame for Learning Essential Collaboration Skills

References

• ASA (2012), “ASA Board Statement on Continuing Professional Development: Its Importance for Statisticians and the Role of the ASA,” Technical Report, American Statistical Association, available at https://www.amstat.org/ASA/files/pdfs/EDU-CPDBoardStatement.pdf.
   Google Scholar
• ASA (2014), “Curriculum Guidelines for Undergraduate Programs in Statistical Science,” Technical Report, American Statistical Association, available at https://www.amstat.org/asa/files/pdfs/EDU-guidelines2014-11-15.pdf.
   Google Scholar
• Azad, K. (2015), Math, Better Explained: Learn to Unlock Your Math Intuition, Scotts Valley, CA: CreateSpace Independent Publishing Platform.
   Google Scholar
• Ben-Zvi, D. (2007), “Using Wiki to Promote Collaborative Learning in Statistics Education,” Technology Innovations in Statistics Education, 1, 1–18.
   Google Scholar
• Blei, D. M., and Smyth, P. (2017), “Science and Data Science,” Proceedings of the National Academy of Sciences of the United States of America, 114, 8689–8692. DOI: 10.1073/pnas.1702076114.
   PubMed Web of Science ®Google Scholar
• Boen, J. R., and Zahn, D. A. (1982), The Human Side of Statistical Consulting, Belmont, CA: Lifetime Learning Publications.
   Google Scholar
• Börner, K., Scrivner, O., Gallant, M., Ma, S., Liu, X., Chewning, K., Wu, L., and Evans, J. A. (2018), “Skill Discrepancies Between Research, Education, and Jobs Reveal the Critical Need to Supply Soft Skills for the Data Economy,” Proceedings of the National Academy of Sciences of the United States of America, 115, 12630–12637. DOI: 10.1073/pnas.1804247115.
   PubMed Web of Science ®Google Scholar
• Boroto, D. R., and Zahn, D. A. (1989), “On Becoming Valued and Utilized,” The American Statistician, 43, 71–72. DOI: 10.1080/00031305.1989.10475618.
   Web of Science ®Google Scholar
• Cabrera, J., and McDougall, A. (2002), Statistical Consulting, New York: Springer.
   Google Scholar
• Chatfield, C. (1995), Problem Solving: A Statistician’s Guide (2nd ed.), Boca Raton, FL: CRC Press.
   Google Scholar
• COPE (2018), “Ethical Guidelines for Statistical Practice,” Technical Report, Committee on Professional Ethics of the American Statistical Association, available at https://www.amstat.org/ASA/Your-Career/Ethical-Guidelines-for-Statistical-Practice.aspx.
   Google Scholar
• Covey, S. R. (1989), The Seven Habits of Highly Effective People: Restoring the Character Ethic, New York: Simon and Schuster.
   Google Scholar
• Degani, A., and Wiener, E. L. (1993), “Cockpit Checklists: Concepts, Design, and Use,” Human Factors, 35, 345–359. DOI: 10.1177/001872089303500209.
   Web of Science ®Google Scholar
• Derr, J. (2000), Statistical Consulting: A Guide to Effective Communication, Pacific Grove, CA: Duxbury Press.
   Google Scholar
• Epstein, R. M., and Hundert, E. M. (2002), “Defining and Assessing Professional Competence,” JAMA, 287, 226–235. DOI: 10.1001/jama.287.2.226.
   PubMed Web of Science ®Google Scholar
• Gawande, A. (2009), The Checklist Manifesto: How to Get Things Right (1st ed.), New York, NY: Metropolitan Books.
   Google Scholar
• Glaze, J. E. (2001), “Reflection as a Transforming Process: Student Advanced Nurse Practitioners’ Experiences of Developing Reflective Skills as Part of an MSc Programme,” Journal of Advanced Nursing, 34, 639–647. DOI: 10.1046/j.1365-2648.2001.01793.x.
   PubMed Web of Science ®Google Scholar
• Goleman, D. (2006), Social Intelligence: The New Science of Human Relationships, New York: Random House Publishing Group.
   Google Scholar
• Goleman, D. (2012), Emotional Intelligence: Why It Can Matter More Than IQ, New York: Random House Publishing Group.
   Google Scholar
• Hahn, H. A. (2014), “Engineering Sciences Strategic Leadership Plan,” Technical Report LA-UR-14-20973, Los Alamos National Lab. (LANL), Los Alamos, NM (United States), available at https://www.osti.gov/biblio/1120722.
   Google Scholar
• Hall, S., and Vance, E. A. (2010), “Improving Self-Efficacy in Statistics: Role of Self-Explanation & Feedback,” Journal of Statistics Education, 18, 1–22. DOI: 10.1080/10691898.2010.11889583.
   Google Scholar
• Hand, D. J., and Everitt, B. S. (2007), The Statistical Consultant in Action, Cambridge: Cambridge University Press.
   Google Scholar
• Hersey, P., and Blanchard, K. H. (1969), “Life Cycle Theory of Leadership,” Training & Development Journal, 23, 26.
   Google Scholar
• Hersey, P., and Blanchard, K. H. (1977), Management of Organizational Behavior: Utilizing Human Resources, Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Hersey, P., and Blanchard, K. H. (1996), “Revisiting the Life-Cycle Theory of Leadership,” Training and Development, 50, 42–47.
   Google Scholar
• Hoadley, A. B., and Kettenring, J. R. (1990), “Communications Between Statisticians and Engineers/Physical Scientists,” Technometrics, 32, 243–247. DOI: 10.2307/1269092.
   Web of Science ®Google Scholar
• Holyoak, K. J., and Thagard, P. (1995), Mental Leaps: Analogy in Creative Thought, Cambridge, MA: MIT Press.
   Google Scholar
• Jeske, D. R., Lesch, S. M., and Deng, H. (2007), “The Merging of Statistics Education, Consulting and Research: A Case Study,” Journal of Statistics Education, 15, 1–19. DOI: 10.1080/10691898.2007.11889544.
   Google Scholar
• Kettenring, J. R., Koehler, K. J., and McKenzie, J. D., Jr. (2015), “Challenges and Opportunities for Statistics in the Next 25 Years,” The American Statistician, 69, 86–90. DOI: 10.1080/00031305.2015.1033987.
   Web of Science ®Google Scholar
• Khachatryan, D. (2015), “Incorporating Statistical Consulting Case Studies in Introductory Time Series Courses,” The American Statistician, 69, 387–396. DOI: 10.1080/00031305.2015.1026611.
   Web of Science ®Google Scholar
• Kimball, A. W. (1957), “Errors of the Third Kind in Statistical Consulting,” Journal of the American Statistical Association, 52, 133–142. DOI: 10.1080/01621459.1957.10501374.
   Web of Science ®Google Scholar
• Leman, S., House, L., and Hoegh, A. (2015), “Developing a New Interdisciplinary Computational Analytics Undergraduate Program: A Qualitative-Quantitative-Qualitative Approach,” The American Statistician, 69, 397–408. DOI: 10.1080/00031305.2015.1090337.
   Web of Science ®Google Scholar
• Lesser, L. M., and Nordenhaug, E. (2004), “Ethical Statistics and Statistical Ethics: Making an Interdisciplinary Module,” Journal of Statistics Education, 12, 1–26. DOI: 10.1080/10691898.2004.11910630.
   Google Scholar
• Love, K., Vance, E. A., Harrell, F. E., Johnson, D. E., Kutner, M. H., Snee, R. D., and Zahn, D. (2017), “Developing a Career in the Practice of Statistics: The Mentor’s Perspective,” The American Statistician, 71, 38–46. DOI: 10.1080/00031305.2016.1255257.
   Web of Science ®Google Scholar
• Mann, K., Gordon, J., and MacLeod, A. (2007), “Reflection and Reflective Practice in Health Professions Education: A Systematic Review,” Advances in Health Sciences Education, 14, 595–621. DOI: 10.1007/s10459-007-9090-2.
   PubMed Web of Science ®Google Scholar
• Martin, M. A. (2003), “‘It’s Like… You Know’: The Use of Analogies and Heuristics in Teaching Introductory Statistical Methods,” Journal of Statistics Education, 11, 1–28.
   Google Scholar
• Mullen, Z., Wiens, A., Vance, E., and Lovejoy, H. (2019), “Mapping the Uncertainty of 19th Century West African Slave Origins Using a Markov Decision Process Model,” arXiv no. 1908.00431.
   Google Scholar
• Murdoch, W. J., Singh, C., Kumbier, K., Abbasi-Asl, R., and Yu, B. (2019), “Interpretable Machine Learning: Definitions, Methods, and Applications,” arXiv no. 1901.04592.
   Google Scholar
• National Academies of Sciences, Engineering, and Medicine (2018a), Data Science for Undergraduates: Opportunities and Options, Washington, DC: The National Academies Press.
   Google Scholar
• National Academies of Sciences, Engineering, and Medicine (2018b), Graduate STEM Education for the 21st Century, Washington, DC: The National Academies Press.
   Google Scholar
• Nesbit, P. L. (2012), “The Role of Self-Reflection, Emotional Management of Feedback, and Self-Regulation Processes in Self-Directed Leadership Development,” Human Resource Development Review, 11, 203–226. DOI: 10.1177/1534484312439196.
   Web of Science ®Google Scholar
• Palmer, L. (2014), “ASA Launches Personal Skills Development Program,” Amstat News, 443, 131.
   Google Scholar
• Pearl, J. (1995), “Causal Diagrams for Empirical Research,” Biometrika, 82, 669–688. DOI: 10.1093/biomet/82.4.669.
   Web of Science ®Google Scholar
• Podolefsky, N. S., and Finkelstein, N. D. (2007), “Analogical Scaffolding and the Learning of Abstract Ideas in Physics: Empirical Studies,” Physical Review Special Topics—Physics Education Research, 3, 020104.
   Google Scholar
• Schön, D. A. (1983), The Reflective Practitioner: How Professionals Think in Action, New York, NY: Basic Books.
   Google Scholar
• Snee, R. D. (1998), “Non-Statistical Skills That Can Help Statisticians Be More Effective,” Total Quality Management, 9, 711–722. DOI: 10.1080/0954412988181.
   Web of Science ®Google Scholar
• Snee, R. D. (2005), “Leading Business Improvement: A New Role for Statisticians and Quality Professionals,” Quality and Reliability Engineering International, 21, 235–242.
   Web of Science ®Google Scholar
• Stallings, J. (2014), “Type IV Errors: How Collaboration Can Lead to Simpler Analyses,” Amstat News, 440, 24–25.
   Google Scholar
• Stallings, J., Vance, E., Yang, J., Vannier, M. W., Liang, J., Pang, L., Dai, L., Ye, I., and Wang, G. (2013), “Determining Scientific Impact Using a Collaboration Index,” Proceedings of the National Academy of Sciences of the United States of America, 110, 9680–9685. DOI: 10.1073/pnas.1220184110.
   PubMed Web of Science ®Google Scholar
• Vance, E. A. (2015), “Recent Developments and Their Implications for the Future of Academic Statistical Consulting Centers,” The American Statistician, 69, 127–137. DOI: 10.1080/00031305.2015.1033990.
   Web of Science ®Google Scholar
• Vance, E. A. (2018), “LISA: Laboratory for Interdisciplinary Statistical Analysis 2017–18 Annual Report,” Technical Report, University of Colorado Boulder, available at https://osf.io/4fm6p/.
   Google Scholar
• Vance, E. A., Archie, E. A., and Moss, C. J. (2009), “Social Networks in African Elephants,” Computational and Mathematical Organization Theory, 15, 273–293. DOI: 10.1007/s10588-008-9045-z.
   Web of Science ®Google Scholar
• Vance, E. A., and Smith, H. (2016), “Using Video to Improve Your Practice of Statistics,” available at www.osf.io/xmtce.
   Google Scholar
• Vance, E. A., and Smith, H. (2018), “Collaboration Essentials: Asking Great Questions,” available at http://community.amstat.org/cas/new-item/new-item7.
   Google Scholar
• Vance, E. A., and Smith, H. (2019), “Public files for Collaboration in a Bag,” available at https://osf.io/xmtce/.
   Google Scholar
• Vance, E. A., Xie, X., Henry, A., Wernz, C., and Slonim, A. D. (2013), “Computed Tomography Scan Use Variation: Patient, Hospital, and Geographic Factors,” The American Journal of Managed Care, 19, e93–99.
   PubMed Web of Science ®Google Scholar
• Yu, B., and Kumbier, K. (2019), “Three Principles of Data Science: Predictability, Computability, and Stability (PCS),” arXiv no. 1901.08152.
   Google Scholar
• Zahn, D. (2019), Stumbling Blocks to Stepping Stones, Bloomington, IN: iUniverse.
   Google Scholar