Southern Utah University

Course Syllabus

Southern Utah University
Southern Utah University
Spring Semester 2026

Research Methods in Political Science (Face-to-Face)

POLS 2000-01

Course: POLS 2000-01
Credits: 3
Term: Spring Semester 2026
Department: PSCJ
CRN: 12603

Course Description

Methods and approaches of social science and political science, including theory and techniques of qualitative and quantitative research design. (Spring) [Graded (Standard Letter)] Co-requisite(s): POLS 2005 Registration Restriction(s): None

Required Texts

First is Statical Inference via Data Science: A ModernDrive into R and the Tidyverse by Chester Islay and Albert Y. Kim (MD in syllabus)



Second is Data Analysis for Social Science: A Friendly and Practical Introduction by Elena Llaudet and Kosuke Imai (DSS in syllabus)


You must download the following software:


Learning Outcomes

Successful students will:

  • Acquire and/or further develop knowledge of basic statistical tools, such as the histograms, average, standard deviation, normal approximation, scatterplots, correlation, simple and multiple regression, sample survey, and hypothesis tests;
  • Understand basic concepts in probability theory, such as conditional probability, the law of averages, the expected value, and the standard error;
  • Develop knowledge of how to use basic programming in R to implement statistical tools;
  • Learn how to evaluate empirical arguments;
  • Explain data and analyses in a clear and convincing way.

Course Requirements

All assignments must be generated using either RMarkdown or Quarto unless noted.

Data Assignments 


You will have numerous data assignments posted on Canvas. These will test your understanding of the concepts covered in class. These are due on Friday at 11:59 PM. The assignments are worth 25% of your grade. 

Lab Work


  Throughout this semester you will have to do numerous lab assignments. You will not get a worksheet to do these. These will be graded based on completion. You have to follow along with the lecture and complete these assignments yourself in order to get credit. These are worth 25% of your grade. You must get above 70% on this portion of your grade in order to pass pols 2005

Final Project


You will find some real-world data and answer a question that is interesting to you. Possible questions could be public opinion and political behavior, racial biases in police behavior, professional athlete salaries. Your job is to (1) Create a research question (2) Find (machine readable) data (3) Answer your research question with the tools we have learned in class. 

The goal of this assignment is to make it appear like a professional project that an analyst would deliver. Specifically, you will deliver a summary of your research question and the data collected. Then, you will provide visualizations (that you generate) that motivate your research question. You will then provide your results through regression tables and graphs (whatever is appropriate for your analysis). Finally, you will discuss your limitations. 

This is worth 30% of your final grade. You will have to meet with me (can be an email) by the end of the 4th week to discuss your research topic and show that you have your data secured. You will have to provide a visualization by week 7. Week 10 you will have to turn in your first analysis. Your final report is due during finals week. Meeting these three deadlines are worth 10% of your final grade and your final report is worth 20% of your final grade.

Attendance


15% of your final grade

This is a class with a lot of information that will go by very quickly. The lectures are going to be the basic foundation of your knowledge in this class and the class will be difficult to complete without learning those basics. 


Syllabus Quiz: 


You will have to take a quiz on the syllabus due on the Friday of the first week; this is worth 5% of your final grade

Course Outline

      | Reading                                            | Assignments
-----|-------------------------------------------------|----------------------------------
 1   | MD Ch 1: Getting Started with R       | Syllabus Quiz
 2   | MD Ch2-3: Data Viz & Wrangling      | Labs 1 and 2
 3   | DSS Ch 2: Causal Inference             | Lab 3 and Assignment 1
 4   | Causal inference continued              | Assignment 2 and Research question due
 5   | DSS Ch 3: Sampling                         | Lab 4
 6   | MD Ch 4                                           | Lab 5 and Assignment 3
 7   | DSS Ch 4: Regression                      | First Visualization due
 8   | MD Chs 5-6.2: Regression                |
 9   | MD Ch 7: Probability                         | Lab 6 and Assignment 4
 10  | MD Ch 8: Probability                        | Lab 7  and Analysis for final project
 11  | MD Ch 9: Hypothesis Testing           | Assignment 5
 12  | DSS Ch 7: Quantifying Uncertainty  | Assignment 6

Additional applied readings will be assigned as part of assignments and to reinforce topics. 

Instructor's policies on late assignments and/or makeup work

Data Assignments will not be accepted more than 3 days late as I will post the solutions on Canvas. Otherwise, there will be a late penalty of 5% per day with a maximum penalty of 50%

Attendance Policy

With the exception of extreme circumstances, you are expected to be in class

Course Fees

na

Additional Resources

Coding Help
https://rstudio-education.github.io/hopr/index.html
https://posit.co/resources/cheatsheets/ (Important)
https://r4ds.hadley.nz/
https://web.stanford.edu/class/cs109l/unrestricted/resources/google-style.html (Important)

Data Viz:
https://ggplot2-book.org/
https://socviz.co/

R Markdown:
https://bookdown.org/yihui/rmarkdown/
https://quarto.org/docs/guide/

AI Policy

Generative AI can be useful for difficult coding tasks. Therefore, this course adopts the following AI Policy:

The use of generative AI may only be used in the Research Assignment for advanced coding support. Students are required to specify and provide proper citation for any instance where AI was used to generate code in the Research Assignment. Generative AI MAY NOT BE USED to produce any written aspect of the text. All written text must be your own work.

Generative AI MAY NOT BE USED in any capacity for the Problem Sets or the Lab Assignments.

Suspected use of AI will result in a grade of 0 for the assignment.

ADA Statement

Students with medical, psychological, learning, or other disabilities desiring academic adjustments, accommodations, or auxiliary aids will need to contact the Disability Resource Center, located in Room 206F of the Sharwan Smith Center or by phone at (435) 865-8042. The Disability Resource Center determines eligibility for and authorizes the provision of services.

If your instructor requires attendance, you may need to seek an ADA accommodation to request an exception to this attendance policy. Please contact the Disability Resource Center to determine what, if any, ADA accommodations are reasonable and appropriate.

Academic Credit

According to the federal definition of a Carnegie credit hour: A credit hour of work is the equivalent of approximately 60 minutes of class time or independent study work. A minimum of 45 hours of work by each student is required for each unit of credit. Credit is earned only when course requirements are met. One (1) credit hour is equivalent to 15 contact hours of lecture, discussion, testing, evaluation, or seminar, as well as 30 hours of student homework. An equivalent amount of work is expected for laboratory work, internships, practica, studio, and other academic work leading to the awarding of credit hours. Credit granted for individual courses, labs, or studio classes ranges from 0.5 to 15 credit hours per semester.

Academic Freedom

SUU is operated for the common good of the greater community it serves. The common good depends upon the free search for truth and its free exposition. Academic Freedom is the right of faculty to study, discuss, investigate, teach, and publish. Academic Freedom is essential to these purposes and applies to both teaching and research.

Academic Freedom in the realm of teaching is fundamental for the protection of the rights of the faculty member and of you, the student, with respect to the free pursuit of learning and discovery. Faculty members possess the right to full freedom in the classroom in discussing their subjects. They may present any controversial material relevant to their courses and their intended learning outcomes, but they shall take care not to introduce into their teaching controversial materials which have no relation to the subject being taught or the intended learning outcomes for the course.

As such, students enrolled in any course at SUU may encounter topics, perspectives, and ideas that are unfamiliar or controversial, with the educational intent of providing a meaningful learning environment that fosters your growth and development. These parameters related to Academic Freedom are included in SUU Policy 6.6.

Academic Misconduct

Scholastic honesty is expected of all students. Dishonesty will not be tolerated and will be prosecuted to the fullest extent (see SUU Policy 6.33). You are expected to have read and understood the current SUU student conduct code (SUU Policy 11.2) regarding student responsibilities and rights, the intellectual property policy (SUU Policy 5.52), information about procedures, and what constitutes acceptable behavior.

Please Note: The use of websites or services that sell essays is a violation of these policies; likewise, the use of websites or services that provide answers to assignments, quizzes, or tests is also a violation of these policies. Regarding the use of Generative Artificial Intelligence (AI), you should check with your individual course instructor.

Emergency Management Statement

In case of an emergency, the University's Emergency Notification System (ENS) will be activated. Students are encouraged to maintain updated contact information using the link on the homepage of the mySUU portal. In addition, students are encouraged to familiarize themselves with the Emergency Response Protocols posted in each classroom. Detailed information about the University's emergency management plan can be found at https://www.suu.edu/emergency.

HEOA Compliance Statement

For a full set of Higher Education Opportunity Act (HEOA) compliance statements, please visit https://www.suu.edu/heoa. The sharing of copyrighted material through peer-to-peer (P2P) file sharing, except as provided under U.S. copyright law, is prohibited by law; additional information can be found at https://my.suu.edu/help/article/1096/heoa-compliance-plan.

You are also expected to comply with policies regarding intellectual property (SUU Policy 5.52) and copyright (SUU Policy 5.54).

Mandatory Reporting

University policy (SUU Policy 5.60) requires instructors to report disclosures received from students that indicate they have been subjected to sexual misconduct/harassment. The University defines sexual harassment consistent with Federal Regulations (34 C.F.R. Part 106, Subpart D) to include quid pro quo, hostile environment harassment, sexual assault, dating violence, domestic violence, and stalking. When students communicate this information to an instructor in-person, by email, or within writing assignments, the instructor will report that to the Title IX Coordinator to ensure students receive support from the Title IX Office. A reporting form is available at https://cm.maxient.com/reportingform.php?SouthernUtahUniv

Non-Discrimination Statement

SUU is committed to fostering an inclusive community of lifelong learners and believes our university's encompassing of different views, beliefs, and identities makes us stronger, more innovative, and better prepared for the global society.

SUU does not discriminate on the basis of race, religion, color, national origin, citizenship, sex (including sex discrimination and sexual harassment), sexual orientation, gender identity, age, ancestry, disability status, pregnancy, pregnancy-related conditions, genetic information, military status, veteran status, or other bases protected by applicable law in employment, treatment, admission, access to educational programs and activities, or other University benefits or services.

SUU strives to cultivate a campus environment that encourages freedom of expression from diverse viewpoints. We encourage all to dialogue within a spirit of respect, civility, and decency.

For additional information on non-discrimination, please see SUU Policy 5.27 and/or visit https://www.suu.edu/nondiscrimination.

Pregnancy

Students who are or become pregnant during this course may receive reasonable modifications to facilitate continued access and participation in the course. Pregnancy and related conditions are broadly defined to include pregnancy, childbirth, termination of pregnancy, lactation, related medical conditions, and recovery. To obtain reasonable modifications, please make a request to title9@suu.edu. To learn more visit: https://www.suu.edu/titleix/pregnancy.html.

Disclaimer Statement

Information contained in this syllabus, other than the grading, late assignments, makeup work, and attendance policies, may be subject to change with advance notice, as deemed appropriate by the instructor.