There are two versions of this file: an html and a pdf.

Course Information


Number: POS 5737
Term: Fall 2020 Location: Bellamy 102
Day and Time: Thursday, 11:45am-2:15pm
GitHub Organization: POS 5737 (private)
Slack Workspace: pos5737


Name: Carlisle Rainey
E-Mail:, but please use Slack
Office: Zoom
Office Hours: As needed
GitHub: carlislerainey
Slack: carlislerainey

Teaching Assistant

Name: Rob Lytle
E-Mail:, but please use Slack
Office: Zoom
Office Hours: As needed

Course Description

This course introduces students to the basic methods of political science. It focuses on both statistical concepts (e.g., sample surveys) and computation (e.g., tidyverse). This course complements POS 5736 (research design) and 5744 (math). It serves as the foundation for POS 5746 (regression) and 5747 (maximum likelihood).

Course Objectives

In taking this course seriously, you will:

  1. Aquire and/or further develop knowledge of…
    1. basic statistical tools, such as a histogram, average, standard deviation, normal approximation, scatterplot, correlation, simple and multiple regression, sample surveys
    2. basic concepts in probability theory, such as conditional probability, the law of averages, the expected value, the standard error.
    3. advanced concepts in probability (that rely on calculus), such as a pmf or pdf, moments, and the central limit theorem.
    4. basic concepts in inference, such as a point estimate, interval estimate, and hypothesis test.
  2. Aquire and/or further develop the ability to…
    1. develop and present correct, compelling empirical arguments.
    2. use R for statistical computing, including the tidyverse.
    3. rely on a reproducible workflow to move from raw data to final manuscript with R, LaTeX, and rmarkdown.
    4. use git and GitHub to carefully manage the project files.


I recommend buying a hardcopy of the following textbook:

FPP: Freedman, Pisani, and Purves. 2007. Statistics. (4th Edition).

You might also find the following textbooks helpful (but see me before buying):

Gerring: Gerring. 2012. Social Science Methodology: A Unified Framework. (2th Edition).

Healy: Healy. 2018. The Plain Person’s Guide to Plain Text Social Science.

GW: Grolemund and Wickham. 2017. R for Data Science.

Important Deadlines


I assign your grade in the course based on a qualitative assessment of your participation in the course (accounting for quality and frequency), 13 weekly homework assignments (initial submission and re-submission), 13 reviews of another student’s homework assignment, weekly reading quizzes, a final exam, and one research project.

Weekly Work (49 points)

  • You can earn 1 point on each homework assignment for total of 13 points. See the homework rubric for the details. Your grade for each assignment depends on a high-quality initial submission and a thoughtful re-submission based on your reviews. (You can earn an extra 0.25 points for a submission that exceeds expectations.)
  • You can earn 1 point for each review of a fellow student’s homework assignment for total of 13 points. See the review rubric for the details. (You can earn an extra 0.25 points for a review that exceeds expectations.)
  • You can earn 1 point on each weekly reading quiz for a total of 13 points.
  • You can earn 10 points for participation by frequently and thoughtful engaging other students, the instructor, and the TA throughout the semester both in class, in the homework review process, and in our Slack workspace.

Occassional Assignments (51 points)

  • You can earn 21 points on the in-class, closed-book final exam. The design of the exam is TBD.
  • You can earn 30 points on the research project. You should submit a prospectus by October 8 at 11am for feedback and approval. In general, your research project should demonstrate competence with some of the tools we use in the class and includes data, analysis scripts, and a manuscript. (I also recommend it connect closely with your first-year paper.) I’ll share more details when appropriate.

Class Flow

The class is built around weekly homework assignments. Each homework assignment has three phases: a initial submission phase, review phase, re-submission phase. Each week, each student will…

  1. complete and submission the initial version the homework assignment for that week (due Thur. at 11am),
  2. review one classmate’s submission from the previous week (due Thur. at 11am), and
  3. resubmit the assignment from two weeks ago (due Thur. at 11am).


In my view, social science should be a collaborative activity. But in this class, I want you to learn how to do social science, not just do social science. With that somewhat different goal in mind, I want you to work on your own for the homework submission, with one exception. The exception is that I encourage you to seek help by asking questions on Slack. See below for more about getting help.

Seeking Help

If you run into an problem with the materials or homework assignments, please start a discussion on Slack. This creates a written record of the conversation, promotes a more careful conversation, allows others to contribute, and enables me to improve the course materials in response.

At what point should you ask for help? In order to learn, you must struggle some. Ask for help when your struggle begins to turn into frustration. If you become frustrated, please reach out.


In general, I encourage broad sharing of ideas. The more complete and thorough, the better.

I want you to hold back, though, when discussing homework assignments prior to the initial submission (see my remarks above on collaboration). Remember, I want us to learn to do social science. With that in mind, please follow two guidelines (that I borrowed from the guidelines on Stack Overflow) when helping fellow students complete homework assignments:

  1. Try to provide an explanation that leads the asker in the correct direction. Simply providing a complete, thorough, detailed solution typically doesn’t help the asker.
  2. As a default, don’t provide complete code samples. Usually, the asker just needs someone to point them to a specific function, identify a pesky bug, or walk through the problem in the abstract.

University Attendance Policy

Excused absences include documented illness, deaths in the family and other documented crises, call to active military duty or jury duty, religious holy days, and official University activities. These absences will be accommodated in a way that does not arbitrarily penalize students who have a valid excuse. Consideration will also be given to students whose dependent children experience serious illness.

Academic Honor Policy

The Florida State University Academic Honor Policy outlines the University’s expectations for the integrity of students’ academic work, the procedures for resolving alleged violations of those expectations, and the rights and responsibilities of students and faculty members throughout the process. Students are responsible for reading the Academic Honor Policy and for living up to their pledge to “…be honest and truthful and…[to] strive for personal and institutional integrity at Florida State University.” (Florida State University Academic Honor Policy, found at

American’s with Disabilities Act

Students with disabilities needing academic accommodation should:

  1. register with and provide documentation to the Student Disability Resource Center; and
  2. bring a letter to the instructor indicating the need for accommodation and what type.

Please note that instructors are not allowed to provide classroom accommodation to a student until appropriate verification from the Student Disability Resource Center has been provided.

This syllabus and other class materials are available in alternative format upon request.

For more information about services available to FSU students with disabilities, contact the:

Student Disability Resource Center
874 Traditions Way
108 Student Services Building
Florida State University
Tallahassee, FL 32306-4167
(850) 644-9566 (voice)
(850) 644-8504 (TDD)

Course Development

I develop the course materials and website on GitHub. If you see find a problem (even if you don’t see a solution), please open a discussion on Slack.

Syllabus Change Policy

Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice.


None yet.

Creative Commons License
Carlisle Rainey