Honor Code:
Please help each other by exchanging notes for missed class sessions, studying for exams, etc. Students must acknowledge all instances in which generative AI tools were used in an assignment (such as in ideation, research, analysis, editing, debugging, etc.). However, the assignments that you turn in should be your own work. At my discretion, any form of violation will result in a "zero" score for that particular assignment or an "F" for the course.
Grading:
Homework: 45%
Quiz: 10%
Mid-term Presentation: 15%
Final Research Paper: 25%
Attendance: 10%
A+:100~90; A:89~85; A-:84~80; B+:79~77; B: 76~73; B-:72~70
Please see the attached "Statistical Literacy Rubrics" for the assessment criteria of all assignments (i.e., homework, presentations, and the final paper).
Mid-term Presentation
Students will form research groups with a maximum of 5 students per group. Each group is required to present a preliminary research project of its choice in Week 13. The project should be related to the final research paper. A typical presentation includes:
1. A brief review of literature - at least one paper related to the intended research questions and using multivariate analysis should be reviewed and discussed in the presentation.
2. Research questions/hypotheses
3. Data utilized - the data set should be appropriate for the intended multivariate analysis
4. Preliminary data analyses and results - The focus is only on the statistical method under concern.
The presentation should last at most 15 minutes.
Final research paper
The course requires each group to use a data set on a topic of their choice. The data set should preferably contain many observations and variables. The task is to develop a series of research hypotheses based on theory or past empirical evidence and then apply some of the multivariate techniques covered in class to such data for testing them.
|