Instructor: Kosuke Imai
Description of Course Goals and Curriculum
- Gain hands-on experience and develop confidence working with real-world data sets
- Think critically about how we can learn that A causes B in a social science setting
- Learn and practice basic coding skills in R
- Gain exposure to some of the probability concepts that underlie statistics
Learning From Classroom InstructionLectures generally reviewed the statistics concepts covered in the textbook readings, while precepts covered hands-on activities and in some way served as guided "practice" for the problem sets. Since lectures are so large, precepts offered a better chance to ask questions and engage with the course material. This class requires you to learn new skills, not just concepts. (It's a little bit like a language class in that way.) Learning skills takes active practice, not just studying information. Lecture is useful for exposure to concepts, but won't really help you log much practice time.
Learning For and From Assignments
- Material and code covered in precept often comes up with just a slight twist in the problem sets. Similarly, questions covered on problem sets are likely to be seen again on a take-home exam with a further twist. Learning to recognize when the same concepts are being asked about in a different setting can be helpful.
- While it might be possible to complete book assignments without having read the whole textbook section (and just skimming through to find the relevant bits of code), that approach isn't likely to have served you well when it comes to a problem set or a take-home exam. In many courses actually reading the textbook might not be critical so long as you attend lecture, but the book for this course is very rich, and reading it carefully and following along with every line of code can be a very effective way to learn the material. The book assignments will probably be much easier and you'll get more out of them if you carefully read the textbook before starting.
- Preceptors: The preceptors for this class were awesome and went above and beyond what was expected of them, hosting extra office hours and long review sessions before the exams. Their office hours were a great place to get help with problem sets or ask questions about concepts from lecture. We were free to check out other preceptors' office hours to find the best fit for our learning styles and schedules.
- McGraw: McGraw offers study hall and individual tutoring for this course. Study halls can sometimes get crowded the week a problem set is due, but that makes it a good place to find other people to work and check answers to problem sets with. Additionally, tutors have had practice helping students learn to spot bugs in their code as well as explain challenging concepts.
What Students Should Know About This Course For Purposes Of Course Selection
- This course has many different components, and it will likely be a lot of work. The sheer amount you're asked to do may be a challenge to keep up with.
- The first two weeks will probably be the hardest if you've never coded before. It's a steep learning curve and many people feel overwhelmed at first. However, even though it might not seem like it, most people taking this class don't have coding experience and everyone struggles so don't be afraid to ask a lot of questions. I'd encourage shoppers to stick it out past the first assignment. Debugging code is a skill that develops with practice just like any other.
- Having AP Statistics from high school is useful background and will probably help you understand some topics, but overall this course is very different. AP Stats is a lot of calculator, paper-and-pencil work, whereas this course focuses on hands-on experience with real data.
- There are many other options for politics majors needing to fulfill the analytical requirement, but the material covered in this course and the experience manipulating real-world data in R could be very, very useful for any data analysis you might do in future independent work. (The final project involved finding a data set we were personally interested in and analyzing it. For me, this turned out to be fantastic practice for my JP and thesis.)
Quantitative Analysis and Politics