Description of Course Goals and Curriculum
The goal of the course is to give students a better understanding of statistical concepts and how they might be applied to examine questions of interest. To this effect, the course seeks to create multiple opportunities for students to practice initiating their own research projects by coming up with their own questions and utilizing the statistical and coding tools learned in class to tease out a potential answer to such questions. Since the course is ultimately a statistics course, there is no specific content based theme throughout the class; in fact, the course allows students great freedom to investigate the topics they are interested in, as long as they have a social or political basis.
Learning From Classroom Instruction
The course is broken up into lecture and precept. Lecture material is very closely linked to the assigned readings. Differently, precept consist of a weekly in class exercise. Although the fact that the lecture materials and the reading materials are very similar, this should not be an excuse to not do the readings. Since there are a lot of complicated concepts to cover, lecture tends to go by very quickly and it is hard to follow along and gain intuition if there is no pre-lecture knowledge or at least familiarity with the concepts. In other words, it is helpful that lecture reviews reading materials instead of introducing completely new information, yet lectures can be quite challenging without completing the readings beforehand. Further, it is very important to attend precept, as before the weekly exercise is introduced, the hardest concepts from lecture are typically reviewed, and this is the student’s opportunity to ask questions about them. In addition, the precept assignment tends to be very closely linked to the problem set for the respective week. The understanding of the concepts and code used for the precept assignment usually translates to an ability to finish the problem set faster and understand the concepts explored in it better. In short, it is important to attend precept and carefully examine precept assignments preferably before starting the week’s problem set.
Learning For and From Assignments
As discussed above, the class administers weekly problem sets. In addition, there are four reports over the course of the semester. Problem sets are time consuming, so the student should try to start early as to be able to ask questions about the problem set either after lecture, over email or during office hours. The student should not hesitate to reach out for help, as with statistical concepts and coding, it is often the case that problems that can be easily understood after the clarification from a preceptor of professor, can take several hours if not inquired about. Problem sets are key to solidifying the material learned, so although collaboration is allowed, it is greatly important that the student has an independent understanding of the concepts as collaboration is not allowed for the last two reports. The reports are an opportunity for the student to take the data given by the instructors, and use some of the variables in it to apply the methods learned in class to explore a question of the student’s interest. Overall, the reports are in order of increasing difficulty. The first two reports are in groups of 3, and the last two reports are to be independently completed. Given this, it is very important for the student to, even if the work is divided among group members, know how to do all the main parts of a report. For instance, even if someone was in charge of downloading and cleaning the data, everyone in the group should know how to do it, as when the time for independent reports come, something as simple as downloading the data can become challenging if not put in practice or discussed with someone beforehand.
As mentioned above, preceptor office hours are useful. Even if the student has a good grasp of the material, approaching preceptors when thinking about reports, and brainstorming with them what questions to ask and which methods seem appropriate and realistic to implement can make the task much easier and enjoyable. The professor office hours are useful as well. Since Prof. Wasow is incredibly good at explaining statistical concepts and giving intuition for them, it is better to save coding and more mechanical questions for the precept or preceptor’s office hours, and to ask the more conceptually rooted ones to Prof. Wasow.
In regards to out of class resources, there is no official McGraw tutoring for POL 346, but there is R tutoring every week. Although the tutors will probably not be familiar with the week to week POL 346 material, they can certainly help with coding issues, and many of them might have even taken the class before as well.
What Students Should Know About This Course For Purposes Of Course Selection
As Prof. Wasow himself likes to say, this course serves as a boot camp for junior papers and senior thesis if the student is interested in applying quantitative methods to them. From my own experience, this has in fact been the case, and furthering my statistical and coding knowledge beyond POL 345 (the first part of the sequence) has been indeed greatly beneficial particularly as I write my junior paper, and start thinking about my thesis work. With a weekly problem set and four reports, the class is demanding, and in order to get the most out of it, care should be taken to dedicate the necessary time. Having taken POL 345 is greatly helpful as the transition is a smooth one.