Summer 2020 - POL 201 J100
Introductory Quantitative Methods in Political Science (4)
Class Number: 4014
Delivery Method: In Person
Course Times + Location:
Th 5:30 PM – 8:20 PM
REMOTE LEARNING, Burnaby
Exam Times + Location:
Aug 13, 2020
11:59 PM – 11:59 PM
TAKE HOME-EXAM, Burnaby
Corequisites:POL 200W or permission of department.
Introduces quantitative research techniques in political science. Introduces important analytical and conceptual skills necessary to understand and evaluate quantitative political science research. Quantitative.
This course introduces students to basic statistics and regression techniques, which are the primary analytical methods used in political science research. Political science is largely an empirical discipline and students are expected to develop the ability to read, interpret and evaluate quantitative data used in political science and apply basic empirical analysis skills such as data presentation, statistical inference, and regression analysis. Specifically, this course has three main goals:
1) providing students with an overview of descriptive and inferential statistics, with emphasis on applications to political science;
2) exposing students to common and useful statistical techniques relevant to political science research;
3) familiarizing students with a statistical analysis software commonly used in political science: R-Studio.
Throughout the semester, students will gain an understanding of fundamental techniques in quantitative methods and become equipped with the tools to conduct data analysis through the use of statistical software. In doing so, this course will prepare the students to better understand how political scientists conduct research in the field. Students will also acquire important analytical skills to assess and evaluate political events. POL 201 is one of the foundational courses in the Department’s Research Methods & Analysis Learning Track: http://www.sfu.ca/politics/undergraduate/learning-streams.html
There is one weekly meeting for this class. Each week we will meet for three hours. The first two hours will be the lecture component of the course and the final hour will be the lab tutorial component.
- Lab Quizzes 15%
- In-Class Exams (2) 20%
- Take Home Exam 30%
- Homework 35%
This portion of your grade will be gauged by weekly quizzes during lab (there may be a couple of weeks throughout the semester where you do not have a quiz but you should expect to have a quiz almost every week). The quiz questions will be on material that we covered in the previous lecture or week. These quizzes are designed to encourage attendance and for you to keep up with the course material on a regular basis – two important determinants of getting a good grade in this class!
There will be three exams in this class: two in-class exams and one take-home exam. The in-class exams are not cumulative and most of the questions on the will be math-based and analytical. You should bring a calculator with you on the day of the exams. The take-home exam is cumulative and you will be required to do data analysis using various datasets.
Throughout the semester students will be assigned four homework assignments in lab, which will require them to work with R-Studio. Students will have a week to complete them once they have been assigned. Homework assignments are designed to get the students more comfortable working with R-Studio. Homework assignments are due at the beginning of the lab tutorial session. Late assignments will no be accepted and will automatically receive a grade of 0.
Agresti, Alan. Statistical Methods for the Social Sciences, 5th Edition, University of Florida, 2018.
ISBN: 13: 9780134512822
Department Undergraduate Notes:
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
TEACHING AT SFU IN SUMMER 2020Please note that all teaching at SFU in summer term 2020 will be conducted through remote methods. Enrollment in this course acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.
Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (email@example.com or 778-782-3112) as soon as possible to ensure that they are eligible and that approved accommodations and services are implemented in a timely fashion.