Course Assignments

a) Participation & Practical Applications: Participation & Practical applications will be employed to assess knowledge assimilation and to amplify important concepts from lectures. This is based on best-practices to enhance learning, especially in online environments. You will have the opportunity to earn participation points in class by answering live online polling questions (Poll Ev). Class will be interactive, with an average of 4-8 questions per class meeting to provide a check-on-learning to help assess your own (and the class’s) understanding of statistical concepts and to support your learning. For participation credit, you will earn full credit for responding with any answer, and the live discussion will be used to clarify any content when answers are not in alignment. This may also include discussion in the zoom chat. And we always encourage active live participation in chat and on camera!

Participation will be live-streamed and interactive; so, if you miss class, you are responsible for reviewing the material. Attendance at all classes is preferred, however you may miss up to 3 class meetings for presentations, illness, etc. (~15% of participation points) and still receive full credit (The lowest 3 participation grades will be dropped at the end of the semester). While formal permission is not required for these absences, we would appreciate a courtesy notification if you know in advance that you will be absent. If you are ill for more than 3 classes, please communicate with us so we can work with you to come up with a 1-on-1 customized plan to help keep you on track for the semester. Similarly, if instructors need to cancel or change the schedule due to unexpected illness or closures, we will provide as much notice as possible via Canvas. Please be sure your email notifications are turned on during the semester.

While the virtual format expands accessibility and increases class capacity to serve all of you, we also realize that some of you may be working from home, the lab, or other locations where your internet access or ability to participate may be disrupted – please let us know if this is the case. We realize that you may have disruptions to deal with. Given that, we highly recommend minimizing other electronic distractions (e.g., email, social media, etc.) to get the most out of the class.

b) Tutorial Assignments: Pre-recorded tutorials will be used to familiarize you with how to use and navigate GraphPad Prism. There will be 5 assignments that correspond to each tutorial using pre-assigned data sets. Detailed information about each assignment, with links to videos and data sets, is found under the Assignments Tab in Canvas. Completion of the assignment requires submission of a slide of your output and results from the tutorial to Canvas including a short written response to a prompt. Discussion of the assignments will occur in the class immediately after the Assignment is due and assignments will be graded based on the content on the final submitted slide so late submissions are not permitted.

c) Final Project: A final project will be due at the end of the course. The final project will involve using an advanced statistical method discussed in the class to analyze a real-world data set collected from your own research experiences or from your lab (e.g., lab/thesis/rotation project). The data selected must be sufficiently complex so as to allow you to apply at least one method discussed during the course to apply inferential statistics (e.g., multiple t-tests, ANOVA, regression, survival curves). The final project should include a written description of your analysis that includes: 1) how the data were collected, 2) the hypotheses that you tested, including a null hypothesis 3) descriptive statistics and frequency distributions of the data, 4) treatment of outliers if there are any, 5) statistical methods used to analyze the data and your justification, 6) power calculation and explanation of sample size choice, and 7) the results and conclusions of your analysis. The writing style should be suitable for a scientific journal and should be approximately 2 pages in length. To mimic real-world peer review, you will be asked to submit a draft Final Project, will give and get reviewer feedback from 2 peers. The semester will culminate in the submission of a Final Draft and Final Peer Review. Hence, each person will complete an individual draft and final project and 4 peer reviews, in accordance with the following grading scheme (final project grade is out of 100%): a full draft (30%), 2 peer-ratings of drafts (20%), final project (30%), and 2 peer-ratings of final projects (20%).