WHO SHOULD TAKE THIS COURSE?
This course is designed for students who are interested in developing skills for working with data and using statistical tools to analyze them. No prior experience with data or statistics is required.
WHAT ELSE SHOULD YOU KNOW?
The approach is “statistics in the service of questions”. As such, the research question that you choose (from data sets made available to you) is of paramount importance to your learning experience. It must interest you enough that you will be willing to spend many hours reading about it, thinking about it and analyzing data having to do with it.
The course will offer a focused hands-on experience in the research process. You will develop skills in 1) generating testable hypotheses; 2) conducting a literature review; 3) understanding large data sets; 4) formatting and managing data; 5) conducting descriptive and inferential statistical tests; and 6) reporting and interpreting results.
COURSE REQUIREMENTS
Weekly Class Sessions: Tuesday and Thursday class sessions include instructor and peer mentor support aimed at helping you to make consistent and meaningful progress on your research project. Attendance during these sessions is required for the duration of our time block and is part of your class participation grade.
Materials: All supporting materials for the course will be made available through this website. Moodle will be used for assignment submissions.
Lessons: Rather than a traditional textbook, this course provides a series of “lessons” aimed at preparing students conceptually and technically for the various steps taken in completing their research project. Lessons are presented in video with corresponding text and content/demonstrations. All lessons should be completed prior to each class session.
Quizzes: After reviewing each lesson, you will be asked to complete a brief quiz. These must be completed prior to the associated class session to receive credit.
Blog Entires and Project Component Assignments: Students will submit blog entries through moodle. The purpose of the blog is to encourage you to reflect on the research process, both in terms of concept and execution. You should describe your decisions, observations, learning and experiences as precisely as possible, paying attention to details (e.g. what you accomplished, what the process was like, how you felt about it, what you hope to accomplish next, what you wish you would have known, etc.). There are prompts on the website that you can also examine. But you should feel free to include as many questions and as much information as you have. Component assignments will also be submitted as part of your journal entries as a way of building your story around results and next steps. To receive credit, blog entries and component assignments are due on time. To submit your blog in moodle please find “Add new entry to this course” and not “Add new entry”. Make sure you leave the default option selected (Publish to: Anyone on this site). Your blog title should be “Blog Entry 1” or “Blog Entry 2”, etc. To see all of your published blog entries (or to edit existing ones) go into moodle and search for the Blog Menu (“View my entries about this course”).
Drop in Hours: Our Friday time block will be used to provide students with additional support on their projects. All students must attend a minimum of 5 sessions throughout the semester. You must stay for at least one hour on the days you attend. Students are encouraged to attend as often as they need to get additional support. All students should leave the 1-3PM block on Fridays open so that instructors can set appointments with students as deemed necessary. You are responsible for signing in at the sessions.
Research Plan: Students will prepare and submit a research plan that includes a literature review on their research topic, a description of the study method and an evaluation of the potential implications of the research. Outlines are due and should be posted as part of your blog entries. This assignment will be penalized one grade step for each day that it is late (e.g. – to +)]. For example, a B+ paper submitted after 6 pm on the due date and before 6 pm the following day will receive a B.
Exams: Four quarterly exams will be given during class sessions and will include questions in objective format (i.e. multiple-choice). You will be taking them on your computer during the class period. An instructor will be available to answer any clarifying questions that you have during the exam. In each exam, you will be asked to apply your knowledge and integrate material from lessons and class experiences. These exams are “closed-book”; however, you are permitted to use ONE standard 8.5″x11″ sheet of paper including anything that you think will help you in the exam (your notes may be written on both sides).
Research Poster/Oral Presentation: A final poster session will take place on Friday, May 3rd from 1-3PM. You must be available for the entire 2 hour block. More details about the poster session will be made available in the coming weeks.
Additional Support: Additional tutors are available in the Quantitative Analysis Center throughout the week. Information about accessing this additional support can be found here.
Commitment to the Course: Students are expected to make marked progress each week and to come to class sessions and drop in hours prepared with questions and planned next steps. It is important to note that to really learn the material and skills presented in this course, students will need to devote a substantial amount of time and that a significant portion of that time will likely require support from instructors, mentors, tutors and classmates. Everyone should be taking advantage of one-on-one support throughout the semester.
Scientific Integrity: The rules of science should be carefully upheld in everything that you do. The following behavior is absolutely unacceptable: Data fabrication, selective reporting, omission, suppression or distortion. Please be mindful that there is no such thing as a “little scientific misdemeanor”.
AI Statement The use of AI tools (e.g., ChatGPT, Bing, Elicit, etc.) in completing course assignments is not allowed and constitutes a violation of our honor code.
Accommodations: It is the policy of Wesleyan to provide reasonable accommodations to students with documented disabilities. Students are responsible for registering with Disabilities Services, in addition to making requests known to their instructor. If you require accommodations in this class, please make an appointment with your instructor during the 1st week of the semester, so that appropriate arrangements can be made.
Grades: Course grades will be based on
1. Mini-Assignments and Blog Entries (15%)
2. Quizzes and Survey Participation(5%)
3. Exams (40%, each exam 10%)
4. Research Plan Paper (15%)
5. Class Participation. Regular and punctual attendance (as well as focused effort) at all class sessions. (5%)
6. Research Poster/Oral presentation (20%)
Passing Letter Grades/Percentages:
| A | 95 – 100% |
| A- | 90 – 94.9% |
| B+ | 86.5 – 89.9% |
| B | 84 – 86.4% |
| B- | 80 – 83.9% |
| C+ | 76.5 – 79.9% |
| C | 74 – 76.4% |
| C- | 70 – 73.9% |
| D+ | 66.5 – 69.9% |
| D | 64 – 66.4% |
| D- | 60 – 63.9% |