Statistical Collaboration

Instructors MarioDavidson
Course Number 2022.08.FALL.GS.BIOS.7351.01
Meeting Times Monday 9:00am - 10:00pm and Friday 9:00-11:00
Course Location 11139
TA Shengxin Tu
Office Hours by request

Course Description

  • Goal: To develop the knowledge, skills, attitude, and behavior necessary to interact with research and statistical collaborators.
  • The course will focus on the personal skills and behaviors needed for fruitful collaboration.
  • Professional Expectations
    • Students are expected to - list not all-encompassing:
      • punctually attend all sessions in their entirety and inform the instructor beforehand if unable.
      • have good verbal, physical, and written communication.
      • respect others' space, opportunity to speak (or not), culture, etc.
      • refrain from inappropriate remarks (i.e. swearing, crude, bigoted, sexual, racist, etc. remarks).
      • follow instructions.
      • be responsive and proactive in accomplishing assignments, replying to requests, and providing information.
      • be prepared and alert in class.
      • avoid writing and/or viewing texts, notifications, emails, social media, and other distractions not pertaining to the course.
  • Participation Expectations
    • All students are expected to provide meaningful and/or frequent interactions through blogs, meetings, feedback, questions, debate, discussions, board work, role-playing, large and small group exercises, presentations, projects, constructive criticism, etc.
    • Students should punctually attend all sessions in their entirety and inform the instructor beforehand if unable. (Note: this is a professionalism expectation too.)
    • Students should interact voluntarily.
    • The instructor will monitor participation regularly. It will be assessed relative to other students' performance. Students are given multiple participation grades throughout the semester.
    • While a participation grade may affect behavior, the goal is to have natural, inquisitive, meaningful interactions.
    • When participating through distance learning, cameras and sound are expected to be on.

Course Material, Resources, and Suggestions

Reading material should be completed prior to class. A typesetting language is required. Writing resources may be found at the Vanderbilt Writing Studio. The studio is free for Vanderbilt University students.
  • Text(OPTIONAL): Statistical Consulting: A Guide to Effective Communication, Janice Derr, ISBN-10: 0534362281, ISBN-13: 978-0534362287
    • A copy of the book may be found in the departmental library.
  • Mario A. Davidson, Charlene M. Dewey & Amy E. Fleming (2018) Teaching Communication in a Statistical Collaboration Course: A Feasible, Project-Based, Multimodal Curriculum, The American Statistician, DOI: 10.1080/00031305.2018.1448890

Honor Code

Vanderbilt's Honor Code governs all work in this course. Students may discuss the assignments outside of class, but each student's writing and presentation of the data is expected to be original and independently finalized unless stated otherwise by the instructor. Direct quotes need to cite the source; otherwise, it is considered plagiarism. If you have any questions about the application of the honor code to this course, please ask the instructor.

Assignments and Assessment

Assessments and feedback may be found in Brightspace. Assignments should be dropped into the "Assignment" folder in Brightspace under the appropriate due date and/or topic. All dropped assignments should be an attachment in a typesetting language unless otherwise specified. In Brightspace under the Content/Table of Contents/Calendar of Assignments link, you will find a summary of the assignment deadlines. Recognize that many assignments are due at midnight. More details of the due dates may be found in the appropriate assignment dropbox. Late assignments will be penalized as such: the first day 20%, the second day 40%, and the third day 100%. Assignments may be turned in earlier than the due date. Multiple tardies, early departures, and/or unexcused absences will result in a poor professionalism and participation grade. Failure to inform the instructor in a reasonable amount of time prior to missing class due to previously known situations, events, or barriers is considered an unexcused absence. Emergency situations will be considered on a case-by-case basis.

  • (33%) Projects
  • (20%) Written Statistical Communication Assignments
  • (30%) Presentations
  • (6%) Professionalism (See the Professionalism Expectations above; A "Professional Expectation Rubric" may be found in Brightspace under the "Assignments" link.)
  • (6%) Participation (See the Participation Expectations above.)
  • (5%) Biostatistics Clinic ( https://biostat.app.vumc.org/wiki/Main/Clinics)
Letter grades will be assigned as defined by the following ranges:

Letter Grade Lower Score Upper Score
A+ 96.5 100.0
A 93.5 96.4
A- 90.0 93.4
B+ 86.5 89.9
B 83.5 86.4
B- 80.0 83.4
C+ 76.5 79.9
C 73.5 76.4
C- 70.0 73.4
F 0.0 59.9

Schedule

2022/08/26

  • Introduction

2022/08/29

  • Case 1: Qualities for a Successful Collaboration

2021/09/02

  • Case 1: Qualities for a Successful Collaboration

2022/09/05

  • Asking Good Questions

2021/09/09

  • Challenges of Consulting: Experiences of Real Biostatisticians

2022/09/12

  • Case 2: Statistical Analysis Plan

2022/09/16

  • Case 2: Statistical Analysis Plan

2021/09/19

  • Investigator 1: Regina Russell, PhD

2022/09/23

  • Questionnaire Design
  • Guest Speaker: Frank Harrell, Jr. PhD - Strength in Questioning Collaborator's Assumptions

2022/09/26

  • Delivering an Effective Presentation

2022/09/30

  • Clinic Presentation SAP

2022/10/03

  • Case 3: Professionalism

2022/10/07

  • Case 3: Professionalism

2022/10/10

  • Challenges of Consulting: Experiences of Real Biostatisticians II

2022/10/14

  • Fall Break

2022/10/17

  • Investigator: Travis Crook, MD

2022/10/21

  • Second Clinic Presentation

2022/10/24

  • Communicating About Statistics: Being a Teacher I

2022/10/28

  • Guest Speaker: Bill Dupont, PhD - Grantsmanship
  • Guest Speaker: Bryan Shepherd, PhD - Study Section

2022/10/31

  • Case 4: Supervisor Role and Interviewing

2022/11/04

  • Case 4: Supervisor Role and Interviewing

2022/11/07

  • Poster Design

2021/11/11

  • Department Retreat

2022/11/14

  • Case 5: Ethics

2022/11/18

  • Case 5: Ethics

2022/11/21

  • Thanksgiving Break - no class

2022/11/25

  • Thanksgiving Break - no class

2021/11/28

  • Interview Feedback

2022/12/02

  • Communicating about Statistics: Being a Teacher II
  • Business Aspect: Negotiating a Satisfactory Exchange

2022/12/05

  • Guest Speaker: Meridith Peratikos, MS - Academic vs. Industry Statisticians or Business Aspect II

2022/12/09

  • Poster Presentation (maybe)
  • Conclusion

Access restrictions

Topic revision: r183 - 27 Sep 2022, MarioDavidson
 

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